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ORCIDNigam H. Shah
Nigam Shah – N. H. Shah 0001
Person information
- affiliation: Stanford University, CA, USA
- affiliation (former): Pennsylvania State University, University Park, PA, USA
Other persons with the same name
- N. H. Shah 0002 — Coventry University, UK
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2020 – today
- 2024
[j97]Jenelle A. Jindal
, Matthew P. Lungren, Nigam H. Shah:
Ensuring useful adoption of generative artificial intelligence in healthcare. J. Am. Medical Informatics Assoc. 31(6): 1441-1444 (2024)- [j96]Lin Lawrence Guo, Keith E. Morse, Catherine Aftandilian, Ethan Steinberg, Jason Alan Fries, José D. Posada, Scott Lanyon Fleming, Joshua Lemmon, Karim Jessa, Nigam Shah, Lillian Sung:
Characterizing the limitations of using diagnosis codes in the context of machine learning for healthcare. BMC Medical Informatics Decis. Mak. 24(1): 51 (2024) - [j95]Lin Lawrence Guo, Jason Alan Fries, Ethan Steinberg, Scott Lanyon Fleming, Keith E. Morse, Catherine Aftandilian, José D. Posada, Nigam Shah, Lillian Sung:
A multi-center study on the adaptability of a shared foundation model for electronic health records. npj Digit. Medicine 7(1) (2024) - [j94]Michael Wornow, Avanika Narayan, Krista Opsahl-Ong, Quinn McIntyre, Nigam Shah, Christopher Ré:
Automating the Enterprise with Foundation Models. Proc. VLDB Endow. 17(11): 2805-2812 (2024) - [c77]Scott L. Fleming, Alejandro Lozano, William J. Haberkorn, Jenelle A. Jindal, Eduardo Pontes Reis, Rahul Thapa, Louis Blankemeier, Julian Z. Genkins, Ethan Steinberg, Ashwin Nayak, Birju S. Patel, Chia-Chun Chiang, Alison Callahan, Zepeng Huo, Sergios Gatidis, Scott J. Adams, Oluseyi Fayanju, Shreya J. Shah, Thomas Savage, Ethan Goh, Akshay S. Chaudhari, Nima Aghaeepour, Christopher D. Sharp, Michael A. Pfeffer, Percy Liang, Jonathan H. Chen, Keith E. Morse, Emma P. Brunskill, Jason A. Fries, Nigam H. Shah:
MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records. AAAI 2024: 22021-22030 - [c76]Ethan Steinberg, Jason Alan Fries, Yizhe Xu, Nigam Shah:
MOTOR: A Time-to-Event Foundation Model For Structured Medical Records. ICLR 2024 - [i40]Michael Wornow, Alejandro Lozano, Dev Dash, Jenelle A. Jindal, Kenneth W. Mahaffey, Nigam H. Shah:
Zero-Shot Clinical Trial Patient Matching with LLMs. CoRR abs/2402.05125 (2024) - [i39]Alison Callahan, Duncan C. McElfresh, Juan M. Banda, Gabrielle Bunney, Danton Char, Jonathan H. Chen, Conor K. Corbin, Debadutta Dash, Norman L. Downing, Sneha S. Jain, Nikesh Kotecha, Jonathan Masterson, Michelle M. Mello, Keith E. Morse, Srikar Nallan, Abby Pandya, Anurang Revri, Aditya Sharma, Christopher D. Sharp, Rahul Thapa, Michael Wornow, Alaa Youssef, Michael A. Pfeffer, Nigam H. Shah:
Standing on FURM ground - A framework for evaluating Fair, Useful, and Reliable AI Models in healthcare systems. CoRR abs/2403.07911 (2024) - [i38]Michael Wornow, Avanika Narayan, Krista Opsahl-Ong, Quinn McIntyre, Nigam H. Shah, Christopher Ré:
Automating the Enterprise with Foundation Models. CoRR abs/2405.03710 (2024) - [i37]Louis Blankemeier, Joseph Paul Cohen, Ashwin Kumar, Dave Van Veen, Syed Jamal Safdar Gardezi, Magdalini Paschali, Zhihong Chen, Jean-Benoit Delbrouck, Eduardo Pontes Reis, Cesar Truyts, Christian Bluethgen, Malte Engmann Kjeldskov Jensen, Sophie Ostmeier, Maya Varma, Jeya Maria Jose Valanarasu, Zhongnan Fang, Zepeng Huo, Zaid Nabulsi, Diego Ardila, Wei-Hung Weng, Edson Amaro Júnior, Neera Ahuja, Jason Alan Fries, Nigam H. Shah, Andrew Johnston, Robert D. Boutin, Andrew Wentland, Curtis P. Langlotz, Jason Hom, Sergios Gatidis, Akshay S. Chaudhari:
Merlin: A Vision Language Foundation Model for 3D Computed Tomography. CoRR abs/2406.06512 (2024) - [i36]Michael Wornow, Avanika Narayan, Ben Viggiano, Ishan S. Khare, Tathagat Verma, Tibor Thompson, Miguel Angel Fuentes Hernandez, Sudharsan Sundar, Chloe Trujillo, Krrish Chawla, Rongfei Lu, Justin Shen, Divya Nagaraj, Joshua Martinez, Vardhan Agrawal, Althea Hudson, Nigam H. Shah, Christopher Ré:
Do Multimodal Foundation Models Understand Enterprise Workflows? A Benchmark for Business Process Management Tasks. CoRR abs/2406.13264 (2024) - [i35]Yen Sia Low, Michael L. Jackson, Rebecca J. Hyde, Robert E. Brown, Neil M. Sanghavi, Julian D. Baldwin, C. William Pike, Jananee Muralidharan, Gavin Hui, Natasha Alexander, Hadeel Hassan, Rahul V. Nene, Morgan Pike, Courtney J. Pokrzywa, Shivam Vedak, Adam Paul Yan, Dong-han Yao, Amy R. Zipursky, Christina Dinh, Philip Ballentine, Dan C. Derieg, Vladimir Polony, Rehan N. Chawdry, Jordan Davies, Brigham B. Hyde, Nigam H. Shah, Saurabh Gombar:
Answering real-world clinical questions using large language model based systems. CoRR abs/2407.00541 (2024) - [i34]Ting Fang Tan, Kabilan Elangovan, Jasmine Chiat Ling Ong, Nigam Shah, Joseph Jao-Yiu Sung, Tien Yin Wong, Lan Xue, Nan Liu, Haibo Wang, Chang Fu Kuo, Simon Chesterman, Zee Kin Yeong, Daniel S. W. Ting:
A Proposed S.C.O.R.E. Evaluation Framework for Large Language Models : Safety, Consensus, Objectivity, Reproducibility and Explainability. CoRR abs/2407.07666 (2024) - [i33]Ethan Steinberg, Michael Wornow, Suhana Bedi, Jason Alan Fries, Matthew B. A. McDermott, Nigam H. Shah:
meds_reader: A fast and efficient EHR processing library. CoRR abs/2409.09095 (2024) - 2023
- [j93]Karandeep Singh, Nigam H. Shah, Andrew J. Vickers:
Assessing the net benefit of machine learning models in the presence of resource constraints. J. Am. Medical Informatics Assoc. 30(4): 668-673 (2023) - [j92]Diana Cagliero, Natalie Deuitch, Nigam Shah, Chris Feudtner, Danton Char:
A framework to identify ethical concerns with ML-guided care workflows: a case study of mortality prediction to guide advance care planning. J. Am. Medical Informatics Assoc. 30(5): 819-827 (2023) - [j91]Yizhe Xu, Agata Foryciarz, Ethan Steinberg, Nigam H. Shah:
Clinical utility gains from incorporating comorbidity and geographic location information into risk estimation equations for atherosclerotic cardiovascular disease. J. Am. Medical Informatics Assoc. 30(5): 878-887 (2023) - [j90]Conor K. Corbin, Rob Maclay, Aakash Acharya, Sreedevi Mony, Soumya Punnathanam, Rahul Thapa, Nikesh Kotecha, Nigam H. Shah, Jonathan H. Chen:
DEPLOYR: a technical framework for deploying custom real-time machine learning models into the electronic medical record. J. Am. Medical Informatics Assoc. 30(9): 1532-1542 (2023) - [j89]Joshua Lemmon, Lin Lawrence Guo, Ethan Steinberg, Keith E. Morse, Scott Lanyon Fleming, Catherine Aftandilian, Stephen R. Pfohl, José D. Posada, Nigam Shah, Jason Alan Fries, Lillian Sung:
Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks. J. Am. Medical Informatics Assoc. 30(12): 2004-2011 (2023) - [j88]Michael Wornow, Elsie Gyang Ross, Alison Callahan, Nigam H. Shah:
APLUS: A Python library for usefulness simulations of machine learning models in healthcare. J. Biomed. Informatics 139: 104319 (2023) - [j87]Yizhe Xu, Katelyn K. Bechler, Alison Callahan, Nigam Shah:
Principled estimation and evaluation of treatment effect heterogeneity: A case study application to dabigatran for patients with atrial fibrillation. J. Biomed. Informatics 143: 104420 (2023) - [j86]Michael Wornow, Yizhe Xu, Rahul Thapa, Birju S. Patel, Ethan Steinberg, Scott L. Fleming, Michael A. Pfeffer, Jason Alan Fries, Nigam H. Shah:
The shaky foundations of large language models and foundation models for electronic health records. npj Digit. Medicine 6 (2023) - [c75]Louis Blankemeier, Jason A. Fries, Robert Tinn, Joseph Preston, Nigam Shah, Akshay Chaudhari:
Efficient Diagnosis Assignment Using Unstructured Clinical Notes. ACL (2) 2023: 485-494 - [c74]Shih-Cheng Huang, Zepeng Huo, Ethan Steinberg, Chia-Chun Chiang, Curtis P. Langlotz, Matthew P. Lungren, Serena Yeung, Nigam Shah, Jason Alan Fries:
INSPECT: A Multimodal Dataset for Patient Outcome Prediction of Pulmonary Embolisms. NeurIPS 2023 - [c73]Michael Wornow, Rahul Thapa, Ethan Steinberg, Jason A. Fries, Nigam Shah:
EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models. NeurIPS 2023 - [i32]Ethan Steinberg, Yizhe Xu, Jason A. Fries, Nigam Shah:
Self-Supervised Time-to-Event Modeling with Structured Medical Records. CoRR abs/2301.03150 (2023) - [i31]Conor K. Corbin, Rob Maclay, Aakash Acharya, Sreedevi Mony, Soumya Punnathanam, Rahul Thapa, Nikesh Kotecha, Nigam H. Shah, Jonathan H. Chen:
DEPLOYR: A technical framework for deploying custom real-time machine learning models into the electronic medical record. CoRR abs/2303.06269 (2023) - [i30]Michael Wornow, Yizhe Xu, Rahul Thapa, Birju S. Patel, Ethan Steinberg, Scott L. Fleming, Michael A. Pfeffer, Jason A. Fries, Nigam H. Shah:
The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs. CoRR abs/2303.12961 (2023) - [i29]Debadutta Dash, Rahul Thapa, Juan M. Banda, Akshay Swaminathan, Morgan Cheatham, Mehr Kashyap, Nikesh Kotecha, Jonathan H. Chen, Saurabh Gombar, Lance Downing, Rachel Pedreira, Ethan Goh, Angel Arnaout, Garret Kenn Morris, Honor Magon, Matthew P. Lungren, Eric Horvitz, Nigam H. Shah:
Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery. CoRR abs/2304.13714 (2023) - [i28]Alexey Youssef, Michael Pencina, Anshul Thakur, Tingting Zhu, David A. Clifton, Nigam H. Shah:
All models are local: time to replace external validation with recurrent local validation. CoRR abs/2305.03219 (2023) - [i27]Michael Wornow, Rahul Thapa, Ethan Steinberg, Jason A. Fries, Nigam Shah:
EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models. CoRR abs/2307.02028 (2023) - [i26]Scott L. Fleming, Alejandro Lozano, William J. Haberkorn, Jenelle A. Jindal, Eduardo Pontes Reis, Rahul Thapa, Louis Blankemeier, Julian Z. Genkins, Ethan Steinberg, Ashwin Nayak, Birju S. Patel, Chia-Chun Chiang, Alison Callahan, Zepeng Huo, Sergios Gatidis, Scott J. Adams, Oluseyi Fayanju, Shreya J. Shah, Thomas Savage, Ethan Goh, Akshay S. Chaudhari, Nima Aghaeepour, Christopher D. Sharp, Michael A. Pfeffer, Percy Liang, Jonathan H. Chen, Keith E. Morse, Emma P. Brunskill, Jason A. Fries, Nigam H. Shah:
MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records. CoRR abs/2308.14089 (2023) - [i25]Alejandro Lozano, Scott L. Fleming, Chia-Chun Chiang, Nigam Shah:
Clinfo.ai: An Open-Source Retrieval-Augmented Large Language Model System for Answering Medical Questions using Scientific Literature. CoRR abs/2310.16146 (2023) - [i24]Shih-Cheng Huang, Zepeng Huo, Ethan Steinberg, Chia-Chun Chiang, Matthew P. Lungren, Curtis P. Langlotz, Serena Yeung, Nigam H. Shah, Jason A. Fries:
INSPECT: A Multimodal Dataset for Pulmonary Embolism Diagnosis and Prognosis. CoRR abs/2311.10798 (2023) - [i23]Lin Lawrence Guo, Jason A. Fries, Ethan Steinberg, Scott Lanyon Fleming, Keith E. Morse, Catherine Aftandilian, José D. Posada, Nigam Shah, Lillian Sung:
A Multi-Center Study on the Adaptability of a Shared Foundation Model for Electronic Health Records. CoRR abs/2311.11483 (2023) - 2022
- [j85]Jonathan Lu, Amelia Sattler, Samantha Wang, Ali Raza Khaki, Alison Callahan, Scott L. Fleming, Rebecca Fong, Benjamin Ehlert, Ron C. Li, Lisa Shieh, Kavitha Ramchandran, Michael Gensheimer, Sarah Chobot, Stephen Pfohl, Siyun Li, Kenny Shum, Nitin Parikh, Priya Desai, Briththa Seevaratnam, Melanie Hanson, Margaret Smith, Yizhe Xu, Arjun Gokhale, Steven Lin, Michael A. Pfeffer, Winifred Teuteberg, Nigam H. Shah:
Considerations in the reliability and fairness audits of predictive models for advance care planning. Frontiers Digit. Health 4 (2022) - [c72]Katelyn K. Bechler, Nigam Shah:
Predicting patients who are likely to develop Lupus Nephritis of those newly diagnosed with Systemic Lupus Erythematosus. AMIA 2022 - [c71]Stephen Pfohl, Yizhe Xu, Agata Foryciarz, Nikolaos Ignatiadis, Julian Genkins, Nigam Shah:
Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare. FAccT 2022: 1039-1052 - [c70]Daniel Lopez Martinez, Alex Yakubovich, Martin Seneviratne, Ádám D. Lelkes, Akshit Tyagi, Jonas Kemp, Ethan Steinberg, N. Lance Downing, Ron C. Li, Keith E. Morse, Nigam H. Shah, Ming-Jun Chen:
Instability in clinical risk stratification models using deep learning. ML4H@NeurIPS 2022: 552-565 - [i22]Stephen R. Pfohl, Yizhe Xu, Agata Foryciarz, Nikolaos Ignatiadis, Julian Genkins, Nigam H. Shah:
Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare. CoRR abs/2202.01906 (2022) - [i21]Daniel Lopez Martinez, Alex Yakubovich, Martin Seneviratne, Ádám D. Lelkes, Akshit Tyagi, Jonas Kemp, Ethan Steinberg, N. Lance Downing, Ron C. Li, Keith E. Morse, Nigam H. Shah, Ming-Jun Chen:
Instability in clinical risk stratification models using deep learning. CoRR abs/2211.10828 (2022) - 2021
- [j84]Lin Lawrence Guo, Stephen R. Pfohl, Jason Alan Fries, José D. Posada, Scott L. Fleming, Catherine Aftandilian, Nigam Shah, Lillian Sung:
Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine. Appl. Clin. Inform. 12(4): 808-815 (2021) - [j83]Michael Francis Gensheimer, Sonya Aggarwal, Kathryn R. K. Benson, Justin N. Carter, Solomon Henry, Douglas J. Wood, Scott G. Soltys, Steven Hancock, Erqi Pollom, Nigam H. Shah, Daniel T. Chang:
Automated model versus treating physician for predicting survival time of patients with metastatic cancer. J. Am. Medical Informatics Assoc. 28(6): 1108-1116 (2021) - [j82]Kenneth Jung, Sehj Kashyap, Anand Avati, Stephanie Harman, Heather Shaw, Ron C. Li, Margaret Smith, Kenny Shum, Jacob Javitz, Yohan Vetteth, Tina Seto, Steven C. Bagley, Nigam H. Shah:
A framework for making predictive models useful in practice. J. Am. Medical Informatics Assoc. 28(6): 1149-1158 (2021) - [j81]Tina Hernandez-Boussard, Matthew P. Lungren, Nigam Shah:
Conflicting information from the Food and Drug Administration: Missed opportunity to lead standards for safe and effective medical artificial intelligence solutions. J. Am. Medical Informatics Assoc. 28(6): 1353-1355 (2021) - [j80]Alison Callahan, Vladimir Polony, José D. Posada, Juan M. Banda, Saurabh Gombar, Nigam H. Shah:
ACE: the Advanced Cohort Engine for searching longitudinal patient records. J. Am. Medical Informatics Assoc. 28(7): 1468-1479 (2021) - [j79]Tina Hernandez-Boussard, Matthew P. Lungren, Nigam Shah:
Corrigendum: Conflicting information from the Food and Drug Administration: Missed opportunity to lead standards for safe and effective medical artificial intelligence solutions. J. Am. Medical Informatics Assoc. 28(7): 1600 (2021) - [j78]Birju S. Patel, Ethan Steinberg, Stephen R. Pfohl, Nigam H. Shah:
Learning decision thresholds for risk stratification models from aggregate clinician behavior. J. Am. Medical Informatics Assoc. 28(10): 2258-2264 (2021) - [j77]Lawrence Bai, Madeleine K. D. Scott, Ethan Steinberg, Laurynas Kalesinskas, Aida Habtezion, Nigam H. Shah, Purvesh Khatri:
Computational drug repositioning of atorvastatin for ulcerative colitis. J. Am. Medical Informatics Assoc. 28(11): 2325-2335 (2021) - [j76]Sehj Kashyap, Keith E. Morse, Birju S. Patel, Nigam H. Shah:
A survey of extant organizational and computational setups for deploying predictive models in health systems. J. Am. Medical Informatics Assoc. 28(11): 2445-2450 (2021) - [j75]Stephen R. Pfohl, Agata Foryciarz, Nigam H. Shah:
An empirical characterization of fair machine learning for clinical risk prediction. J. Biomed. Informatics 113: 103621 (2021) - [j74]Ethan Steinberg, Kenneth Jung, Jason A. Fries, Conor K. Corbin, Stephen R. Pfohl, Nigam H. Shah:
Language models are an effective representation learning technique for electronic health record data. J. Biomed. Informatics 113: 103637 (2021) - [j73]Michael Ko, Emma Chen, Ashwin Agrawal, Pranav Rajpurkar, Anand Avati, Andrew Yan-Tak Ng, Sanjay Basu, Nigam H. Shah:
Improving hospital readmission prediction using individualized utility analysis. J. Biomed. Informatics 119: 103826 (2021) - [j72]Alvina Grace Lai, Wai Hoong Chang, Constantinos A. Parisinos, Michail Katsoulis, Ruth M. Blackburn, Anoop D. Shah, Vincent Nguyen, Spiros C. Denaxas, George Davey Smith, Tom R. Gaunt, Krishnarajah Nirantharakumar, Murray P. Cox, Donall Forde, Folkert W. Asselbergs, Steve K. Harris, Sylvia Richardson, Reecha Sofat, Richard J. B. Dobson, Aroon D. Hingorani, Riyaz Patel, Jonathan Sterne, Amitava Banerjee, Alastair K. Denniston, Simon Ball, Neil J. Sebire, Nigam H. Shah, Graham R. Foster, Bryan Williams, Harry Hemingway:
An informatics consult approach for generating clinical evidence for treatment decisions. BMC Medical Informatics Decis. Mak. 21(1): 281 (2021) - [j71]Nigam Shah:
Summarizing Patients Like Mine via an On-demand Consultation Service. Proc. VLDB Endow. 14(13): 3417 (2021) - [c69]Yuan Luo, Fei Wang, Benjamin S. Glicksberg, Jessilyn Dunn, Nigam Shah:
Multi-Modal Data Science for Healthcare: State of the Art, Challenges, and Opportunities. AMIA 2021 - [i20]Stephen R. Pfohl, Haoran Zhang, Yizhe Xu, Agata Foryciarz, Marzyeh Ghassemi, Nigam H. Shah:
A comparison of approaches to improve worst-case predictive model performance over patient subpopulations. CoRR abs/2108.12250 (2021) - [i19]Yuyin Zhou, Shih-Cheng Huang, Jason Alan Fries, Alaa Youssef, Timothy J. Amrhein, Marcello Chang, Imon Banerjee, Daniel L. Rubin, Lei Xing, Nigam Shah, Matthew P. Lungren:
RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR. CoRR abs/2111.11665 (2021) - 2020
- [j70]Mehr Kashyap, Martin G. Seneviratne, Juan M. Banda, Thomas Falconer, Borim Ryu, Sooyoung Yoo, George Hripcsak, Nigam H. Shah:
Development and validation of phenotype classifiers across multiple sites in the observational health data sciences and informatics network. J. Am. Medical Informatics Assoc. 27(6): 877-883 (2020) - [j69]Sehj Kashyap, Saurabh Gombar, Steve Yadlowsky, Alison Callahan, Jason A. Fries, Benjamin A. Pinsky, Nigam H. Shah:
Measure what matters: Counts of hospitalized patients are a better metric for health system capacity planning for a reopening. J. Am. Medical Informatics Assoc. 27(7): 1026-1131 (2020) - [j68]Tina Hernandez-Boussard, Selen Bozkurt, John P. A. Ioannidis, Nigam H. Shah:
MINIMAR (MINimum Information for Medical AI Reporting): Developing reporting standards for artificial intelligence in health care. J. Am. Medical Informatics Assoc. 27(12): 2011-2015 (2020) - [j67]Chunhua Weng, Nigam H. Shah, George Hripcsak:
Deep phenotyping: Embracing complexity and temporality - Towards scalability, portability, and interoperability. J. Biomed. Informatics 105: 103433 (2020) - [j66]Alison Callahan, Ethan Steinberg, Jason A. Fries, Saurabh Gombar, Birju S. Patel, Conor K. Corbin, Nigam H. Shah:
Estimating the efficacy of symptom-based screening for COVID-19. npj Digit. Medicine 3 (2020) - [j65]Ron C. Li, Steven M. Asch, Nigam H. Shah:
Developing a delivery science for artificial intelligence in healthcare. npj Digit. Medicine 3 (2020) - [j64]Adam S. Miner, Albert Haque, Jason A. Fries, Scott L. Fleming, Denise E. Wilfley, G. Terence Wilson, Arnold Milstein, Dan Jurafsky, Bruce A. Arnow, W. Stewart Agras, Li Fei-Fei, Nigam H. Shah:
Assessing the accuracy of automatic speech recognition for psychotherapy. npj Digit. Medicine 3 (2020) - [c68]Vojtech Huser, Clair Blacketer, Karthik Natarajan, Robert T. Miller, Andrew Williams, Selva Muthu Kumaran Sathappan, José D. Posada, Nigam Shah:
Data Quality Assessment of Laboratory Data. AMIA 2020 - [c67]Xu Zuo, Jianfu Li, Bo Zhao, Yujia Zhou, Xiao Dong, Jon D. Duke, Karthik Natarajan, George Hripcsak, Nigam Shah, Juan M. Banda, Ruth M. Reeves, Hua Xu:
Normalizing Clinical Document Titles to LOINC Document Ontology: an Initial Study. AMIA 2020 - [i18]Ethan Steinberg, Kenneth Jung, Jason A. Fries, Conor K. Corbin, Stephen R. Pfohl, Nigam H. Shah:
Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data. CoRR abs/2001.05295 (2020) - [i17]Somalee Datta, José D. Posada, Garrick Olson, Wencheng Li, Ciaran O'Reilly, Deepa Balraj, Joseph Mesterhazy, Joseph Pallas, Priyamvada Desai, Nigam Shah:
A new paradigm for accelerating clinical data science at Stanford Medicine. CoRR abs/2003.10534 (2020) - [i16]Stephen R. Pfohl, Agata Foryciarz, Nigam H. Shah:
An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction. CoRR abs/2007.10306 (2020) - [i15]Jason A. Fries, Ethan Steinberg, Saelig Khattar, Scott L. Fleming, José D. Posada, Alison Callahan, Nigam H. Shah:
Trove: Ontology-driven weak supervision for medical entity classification. CoRR abs/2008.01972 (2020)
2010 – 2019
- 2019
- [j63]Vincent X. Liu, David W. Bates, Jenna Wiens, Nigam H. Shah:
The number needed to benefit: estimating the value of predictive analytics in healthcare. J. Am. Medical Informatics Assoc. 26(12): 1655-1659 (2019) - [j62]Kenneth Jung, Sylvia E. K. Sudat, Nicole Kwon, Walter F. Stewart, Nigam H. Shah:
Predicting need for advanced illness or palliative care in a primary care population using electronic health record data. J. Biomed. Informatics 92 (2019) - [j61]Juan M. Banda, Ashish Sarraju, Fahim Abbasi, Justin Parizo, Mitchel Pariani, Hannah Ison, Elinor Briskin, Hannah Wand, Sébastien Dubois, Kenneth Jung, Seth A. Myers, Daniel J. Rader, Joseph B. Leader, Michael F. Murray, Kelly D. Myers, Katherine Wilemon, Nigam H. Shah, Joshua W. Knowles:
Finding missed cases of familial hypercholesterolemia in health systems using machine learning. npj Digit. Medicine 2 (2019) - [j60]Alison Callahan, Jason A. Fries, Christopher Ré, James I Huddleston III, Nicholas J. Giori, Scott L. Delp, Nigam H. Shah:
Medical device surveillance with electronic health records. npj Digit. Medicine 2 (2019) - [j59]Saurabh Gombar, Alison Callahan, Robert M. Califf, Robert A. Harrington, Nigam H. Shah:
It is time to learn from patients like mine. npj Digit. Medicine 2 (2019) - [c66]Stephen Pfohl, Ben J. Marafino, Adrien Coulet, Fátima Rodriguez, Latha Palaniappan, Nigam H. Shah:
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk. AIES 2019: 271-278 - [c65]Stephen R. Pfohl, Tony Duan, Daisy Yi Ding, Nigam H. Shah:
Counterfactual Reasoning for Fair Clinical Risk Prediction. MLHC 2019: 325-358 - [c64]Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah:
The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data. PSB 2019: 18-29 - [c63]Anand Avati, Tony Duan, Sharon Zhou, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng:
Countdown Regression: Sharp and Calibrated Survival Predictions. UAI 2019: 145-155 - [i14]Albee Y. Ling, Allison W. Kurian, Jennifer L. Caswell-Jin, George W. Sledge Jr., Nigam H. Shah, Suzanne R. Tamang:
A Semi-Supervised Machine Learning Approach to Detecting Recurrent Metastatic Breast Cancer Cases Using Linked Cancer Registry and Electronic Medical Record Data. CoRR abs/1901.05958 (2019) - [i13]Alison Callahan, Jason A. Fries, Christopher Ré, James I Huddleston III, Nicholas J. Giori, Scott L. Delp, Nigam H. Shah:
Medical device surveillance with electronic health records. CoRR abs/1904.07640 (2019) - [i12]Stephen Pfohl, Tony Duan, Daisy Yi Ding, Nigam H. Shah:
Counterfactual Reasoning for Fair Clinical Risk Prediction. CoRR abs/1907.06260 (2019) - [i11]Scott L. Fleming, Kuhan Jeyapragasan, Tony Duan, Daisy Yi Ding, Saurabh Gombar, Nigam Shah, Emma Brunskill:
Missingness as Stability: Understanding the Structure of Missingness in Longitudinal EHR data and its Impact on Reinforcement Learning in Healthcare. CoRR abs/1911.07084 (2019) - [i10]Anitha Kannan, Jason Alan Fries, Eric Kramer, Jen Jen Chen, Nigam Shah, Xavier Amatriain:
The accuracy vs. coverage trade-off in patient-facing diagnosis models. CoRR abs/1912.08041 (2019) - 2018
- [j58]Jason K. Wang, Jason Hom, Santhosh Balasubramanian, Alejandro Schuler, Nigam H. Shah, Mary K. Goldstein, Michael T. M. Baiocchi, Jonathan H. Chen:
An evaluation of clinical order patterns machine-learned from clinician cohorts stratified by patient mortality outcomes. J. Biomed. Informatics 86: 109-119 (2018) - [j57]Chunhua Weng, Nigam Shah, George Hripcsak:
Call for papers: Deep phenotyping for Precision Medicine. J. Biomed. Informatics 87: 66-67 (2018) - [j56]Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Y. Ng, Nigam H. Shah:
Improving palliative care with deep learning. BMC Medical Informatics Decis. Mak. 18(S-4): 55-64 (2018) - [j55]Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Michaela Hardt, Peter J. Liu, Xiaobing Liu, Jake Marcus, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Yi Zhang, Gerardo Flores, Gavin E. Duggan, Jamie Irvine, Quoc Le, Kurt Litsch, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael D. Howell, Claire Cui, Gregory S. Corrado, Jeffrey Dean:
Scalable and accurate deep learning with electronic health records. npj Digit. Medicine 1 (2018) - [c62]Ruijun Chen, Patrick B. Ryan, Karthik Natarajan, Thomas Falconer, Christian G. Reich, Rohit Vashisht, Nigam Shah, George Hripcsak:
Treatment Pathways in Patients with Cancer Using a Large-scale Observational Data Network. AMIA 2018 - [c61]Stephen R. Pfohl, Nigam Shah:
Transfer learning to adapt predictive models for pediatric patients in the EHR. AMIA 2018 - [c60]Martin G. Seneviratne, Juan M. Banda, James D. Brooks, Nigam Shah, Tina Hernandez-Boussard:
Identifying cases of metastatic prostate cancer using machine learning on electronic health records. AMIA 2018 - [c59]Philip R. O. Payne, Nigam H. Shah, Jessica D. Tenenbaum, Lara M. Mangravite:
Session introduction. PSB 2018: 240-246 - [c58]Sarah Poole, Nigam Shah:
Addressing vital sign alarm fatigue using personalized alarm thresholds. PSB 2018: 472-483 - [r2]Nigam Shah:
Biomedical Data/Content Acquisition, Curation. Encyclopedia of Database Systems (2nd ed.) 2018 - [i9]Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Peter J. Liu, Xiaobing Liu, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Gavin E. Duggan, Gerardo Flores, Michaela Hardt, Jamie Irvine, Quoc V. Le, Kurt Litsch, Jake Marcus, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael D. Howell, Claire Cui, Greg Corrado, Jeff Dean:
Scalable and accurate deep learning for electronic health records. CoRR abs/1801.07860 (2018) - [i8]Alejandro Schuler, Nigam Shah:
General-purpose validation and model selection when estimating individual treatment effects. CoRR abs/1804.05146 (2018) - [i7]Anand Avati, Tony Duan, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng:
Countdown Regression: Sharp and Calibrated Survival Predictions. CoRR abs/1806.08324 (2018) - [i6]Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah:
The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data. CoRR abs/1808.03331 (2018) - [i5]Stephen Pfohl, Ben J. Marafino, Adrien Coulet, Fátima Rodriguez, Latha Palaniappan, Nigam H. Shah:
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk. CoRR abs/1809.04663 (2018) - [i4]Anand Avati, Stephen Pfohl, Chris Lin, Thao Nguyen, Meng Zhang, Philip Hwang, Jessica Wetstone, Kenneth Jung, Andrew Y. Ng, Nigam H. Shah:
Predicting Inpatient Discharge Prioritization With Electronic Health Records. CoRR abs/1812.00371 (2018) - 2017
- [j54]Yen S. Low, Aaron C. Daugherty, Elizabeth A. Schroeder, William Chen, Tina Seto, Susan C. Weber, Michael Lim, Trevor Hastie, Maya Mathur, Manisha Desai, Carl Farrington, Andrew A. Radin, Marina Sirota, Pragati Kenkare, Caroline A. Thompson, Peter P. Yu, Scarlett L. Gomez, George W. Sledge, Allison W. Kurian, Nigam H. Shah:
Synergistic drug combinations from electronic health records and gene expression. J. Am. Medical Informatics Assoc. 24(3): 565-576 (2017) - [j53]Rave Harpaz, William DuMouchel, Martijn J. Schuemie, Olivier Bodenreider, Carol Friedman, Eric Horvitz, Anna Ripple, Alfred Sorbello, Ryen W. White, Rainer Winnenburg, Nigam H. Shah:
Toward multimodal signal detection of adverse drug reactions. J. Biomed. Informatics 76: 41-49 (2017) - [c57]Jon D. Duke, George Hripcsak, Patrick B. Ryan, Nigam Shah:
From Large-Scale Network Analytics to Clinical Solutions in OHDSI. AMIA 2017 - [c56]Jason K. Wang, Alejandro Schuler, Nigam Shah, Jonathan H. Chen:
Impact of Clinician Experience on Machine Learned Clinical Order Patterns. AMIA 2017 - [c55]Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Y. Ng, Nigam H. Shah:
Improving palliative care with deep learning. BIBM 2017: 311-316 - [c54]Vibhu Agarwal, Mathew Smuck, Nigam Shah:
Quantifying the relative change in physical activity after Total Knee Arthroplasty using accelerometer based measurements. CRI 2017 - [c53]Juan M. Banda, Yoni Halpern, David A. Sontag, Nigam Shah:
Electronic phenotyping with APHRODITE and the Observational Health Sciences and Informatics (OHDSI) data network. CRI 2017 - [c52]Alejandro Schuler, David A. Wulf, Yun Lu, Jennifer M. Baker, Gabriel J. Escobar, Nigam Shah, Vincent X. Liu:
A novel propensity modeling approach to estimate the causal impact of acute organ dysfunction on long-term survival in sepsis. CRI 2017 - [c51]Sébastien Dubois, Nathanael Romano, Kenneth Jung, Nigam Shah, David C. Kale:
The Effectiveness of Transfer Learning in Electronic Health Records Data. ICLR (Workshop) 2017 - [c50]Vibhu Agarwal, Nigam H. Shah:
Learning Attributes of Disease Progression from Trajectories of Sparse Lab Values. PSB 2017: 184-194 - [c49]Philip R. O. Payne, Kun Huang, Nigam H. Shah, Jessica D. Tenenbaum:
Open Data for Discovery Science. PSB 2017: 649-652 - [i3]Sébastien Dubois, Nathanael Romano, Nigam Shah, Kenneth Jung:
Learning Effective Representations from Clinical Notes. CoRR abs/1705.07025 (2017) - [i2]Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Y. Ng, Nigam H. Shah:
Improving Palliative Care with Deep Learning. CoRR abs/1711.06402 (2017) - 2016
- [j52]Anika Oellrich, Nigel Collier, Tudor Groza, Dietrich Rebholz-Schuhmann, Nigam Shah, Olivier Bodenreider, Mary Regina Boland, Ivo I. Georgiev, Hongfang Liu, Kevin M. Livingston, Augustin Luna, Ann-Marie Mallon, Prashanti Manda, Peter N. Robinson, Gabriella Rustici, Michelle Simon, Liqin Wang, Rainer Winnenburg, Michel Dumontier:
The digital revolution in phenotyping. Briefings Bioinform. 17(5): 819-830 (2016) - [j51]Alison Callahan, Saminda Abeyruwan, Hassan Al-Ali, Kunie Sakurai, Adam R. Ferguson, Phillip G. Popovich, Nigam H. Shah, Ubbo Visser, John L. Bixby, Vance P. Lemmon:
RegenBase: a knowledge base of spinal cord injury biology for translational research. Database J. Biol. Databases Curation 2016 (2016) - [j50]Karin Verspoor, Anika Oellrich, Nigel Collier, Tudor Groza, Philippe Rocca-Serra, Larisa N. Soldatova, Michel Dumontier, Nigam Shah:
Thematic issue of the Second combined Bio-ontologies and Phenotypes Workshop. J. Biomed. Semant. 7: 66:1-66:4 (2016) - [j49]Rainer Winnenburg, Nigam H. Shah:
Generalized enrichment analysis improves the detection of adverse drug events from the biomedical literature. BMC Bioinform. 17: 250 (2016) - [j48]Laura K. Wiley, Peter Tarczy-Hornoch, Joshua C. Denny, Robert R. Freimuth, Casey L. Overby, Nigam Shah, Ross D. Martin, Indra Neil Sarkar:
Harnessing next-generation informatics for personalizing medicine: a report from AMIA's 2014 Health Policy Invitational Meeting. J. Am. Medical Informatics Assoc. 23(2): 413-419 (2016) - [j47]Vibhu Agarwal, Tanya Podchiyska, Juan M. Banda, Veena Goel, Tiffany I. Leung, Evan P. Minty, Timothy E. Sweeney, Elsie Gyang, Nigam H. Shah:
Learning statistical models of phenotypes using noisy labeled training data. J. Am. Medical Informatics Assoc. 23(6): 1166-1173 (2016) - [j46]Sarah Poole, Lee Frederick Schroeder, Nigam Shah:
An unsupervised learning method to identify reference intervals from a clinical database. J. Biomed. Informatics 59: 276-284 (2016) - [c48]Jon D. Duke, Nigam H. Shah, George Hripcsak, Patrick B. Ryan:
Ensuring Reproducibility in Observational Research: Building and Sharing Knowledge Resources in the OHDSI Network. AMIA 2016 - [c47]Jianying Hu, Nigam H. Shah, Bradley A. Malin, Patrick B. Ryan, Anil Jain:
Big Data for Healthcare and Life Sciences: Learning Useful Insights from Imperfect Data. AMIA 2016 - [c46]Rohit Vashisht, Kenneth Jung, Nigam Shah:
Learning Effective Treatment Pathways for Type-2 Diabetes from a clinical data warehouse. AMIA 2016 - [c45]Vibhu Agarwal, Lichy Han, Isaac Madan, Shaurya Saluja, Aaditya Shidham, Nigam Shah:
Predicting hospital visits from geo-tagged Internet search logs. CRI 2016 - [c44]Jon D. Duke, George Hripcsak, Nigam Shah, Patrick B. Ryan, Vojtech Huser:
Observational Health Data Sciences and Informatics (OHDSI): A Rapidly Growing International Network for Open Science and Data Analytics in Healthcare. CRI 2016 - [c43]Justin Norden, Timothy E. Sweeney, Aleksandra Pavlovic, Euan A. Ashley, Nigam Shah, Cindy Kin, Alexander Morgan:
A Pilot Study of the Integration of a Quantified-self Wearable Device with EMR data in the Acute Postoperative Setting. CRI 2016 - [c42]Sarah F. Poole, Shaun J. Grannis, Nigam Shah:
Predicting Emergency Department Visits. CRI 2016 - [c41]Kelly Regan, Zachary B. Abrams, Michael F. Sharpnack, Arunima Srivastava, Kun Huang, Nigam Shah, Philip R. O. Payne:
Session Introduction. PSB 2016: 1-8 - [c40]Alejandro Schuler, Vincent X. Liu, Joe Wan, Alison Callahan, Madeleine Udell, David E. Stark, Nigam H. Shah:
Discovering Patient Phenotypes Using Generalized Low Rank Models. PSB 2016: 144-155 - 2015
- [j45]Larisa N. Soldatova, Nigel Collier, Anika Oellrich, Tudor Groza, Karin Verspoor, Philippe Rocca-Serra, Michel Dumontier, Nigam H. Shah:
Special issue on bio-ontologies and phenotypes. J. Biomed. Semant. 6: 40 (2015) - [j44]Kenneth Jung, Paea LePendu, Srinivasan Iyer, Anna Bauer-Mehren, Bethany Percha, Nigam H. Shah:
Functional evaluation of out-of-the-box text-mining tools for data-mining tasks. J. Am. Medical Informatics Assoc. 22(1): 121-131 (2015) - [j43]Guan Wang, Kenneth Jung, Rainer Winnenburg, Nigam H. Shah:
A method for systematic discovery of adverse drug events from clinical notes. J. Am. Medical Informatics Assoc. 22(6): 1196-1204 (2015) - [j42]Kenneth Jung, Nigam H. Shah:
Implications of non-stationarity on predictive modeling using EHRs. J. Biomed. Informatics 58: 168-174 (2015) - [j41]Olivier C. Curé, Henri Maurer, Nigam H. Shah, Paea LePendu:
A formal concept analysis and semantic query expansion cooperation to refine health outcomes of interest. BMC Medical Informatics Decis. Mak. 15-S(S-1): S8 (2015) - [c39]Atul J. Butte, Nigam Shah, Nicholas P. Tatonetti, Hua Xu, Ping Zhang:
Recent Advances in Computational Drug Repositioning. AMIA 2015 - [c38]Jon D. Duke, George Hripcsak, Nigam Shah, Patrick B. Ryan:
The Value of an Open-Source Observational Research Collaboratory: Results from the OHDSI Initiative. AMIA 2015 - [c37]George Hripcsak, Jon D. Duke, Nigam H. Shah, Christian G. Reich, Vojtech Huser, Martijn J. Schuemie, Marc A. Suchard, Rae Woong Park, Ian Chi Kei Wong, Peter R. Rijnbeek, Johan van der Lei, Nicole Pratt, G. Niklas Norén, Yu-Chuan Li, Paul E. Stang, David Madigan, Patrick B. Ryan:
Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers. MedInfo 2015: 574-578 - [c36]David J. Odgers, Rave Harpaz, Alison Callahan, Gregor Stiglic, Nigam H. Shah:
Analyzing Search Behavior of Healthcare Professionals for Drug Safety Surveillance. Pacific Symposium on Biocomputing 2015: 306-317 - [c35]Juan M. Banda, Tobias Kuhn, Nigam H. Shah, Michel Dumontier:
Provenance-Centered Dataset of Drug-Drug Interactions. ISWC (2) 2015: 293-300 - [i1]Juan M. Banda, Tobias Kuhn, Nigam H. Shah, Michel Dumontier:
Provenance-Centered Dataset of Drug-Drug Interactions. CoRR abs/1507.05408 (2015) - 2014
- [j40]Larisa N. Soldatova, Philippe Rocca-Serra, Michel Dumontier, Nigam H. Shah:
Selected papers from the 16th Annual Bio-Ontologies Special Interest Group Meeting. J. Biomed. Semant. 5(S-1): 1 (2014) - [j39]Srinivasan V Iyer, Rave Harpaz, Paea LePendu, Anna Bauer-Mehren, Nigam H. Shah:
Mining clinical text for signals of adverse drug-drug interactions. J. Am. Medical Informatics Assoc. 21(2): 353-362 (2014) - [j38]Sandy Huang, Paea LePendu, Srinivasan V Iyer, Ming Tai-Seale, David Carrell, Nigam H. Shah:
Toward personalizing treatment for depression: predicting diagnosis and severity. J. Am. Medical Informatics Assoc. 21(6): 1069-1075 (2014) - [c34]Nigam Shah:
Medicine in the age of electronic health records. KDD 2014: 1518 - [c33]Graciela Gonzalez, Kevin Bretonnel Cohen, Robert Leaman, Casey S. Greene, Nigam Shah, Maricel G. Kann, Jieping Ye:
Session introduction. Pacific Symposium on Biocomputing 2014: 312-315 - [c32]Jaewon Yang, Julian J. McAuley, Jure Leskovec, Paea LePendu, Nigam Shah:
Finding progression stages in time-evolving event sequences. WWW 2014: 783-794 - 2013
- [j37]Larisa N. Soldatova, Susanna-Assunta Sansone, Michel Dumontier, Nigam H. Shah:
Selected papers from the 15th Annual Bio-Ontologies Special Interest Group Meeting. J. Biomed. Semant. 4(S-1): I1 (2013) - [j36]Tobias Wittkop, Emily TerAvest, Uday S. Evani, K. Mathew Fleisch, Ari E. Berman, Corey Powell, Nigam H. Shah, Sean D. Mooney:
STOP using just GO: a multi-ontology hypothesis generation tool for high throughput experimentation. BMC Bioinform. 14: 53 (2013) - [j35]Ryen W. White, Nicholas P. Tatonetti, Nigam H. Shah, Russ B. Altman, Eric Horvitz:
Web-scale pharmacovigilance: listening to signals from the crowd. J. Am. Medical Informatics Assoc. 20(3): 404-408 (2013) - [j34]Rave Harpaz, Santiago Vilar, William DuMouchel, Hojjat Salmasian, Krystl Haerian, Nigam H. Shah, Herbert S. Chase, Carol Friedman:
Combing signals from spontaneous reports and electronic health records for detection of adverse drug reactions. J. Am. Medical Informatics Assoc. 20(3): 413-419 (2013) - [c31]Sandy Huang, Paea LePendu, Srinivasan V Iyer, Ming Tai-Seale, David Carrell, Nigam Shah:
Predictive Models in Mental Health: From Diagnosis to Treatment. AMIA 2013 - [c30]Nigam Shah, Paea LePendu, Anna Bauer-Mehren, Srinivasan V Iyer, Kenneth Jung, Tyler Cole, Rave Harpaz:
Learning Practice-based Evidence from Unstructured Clinical Notes. AMIA 2013 - [c29]Olivier Curé, Henri Maurer, Nigam Shah, Paea LePendu:
Refining health outcomes of interest using formal concept analysis and semantic query expansion. DTMBIO 2013: 5-6 - [c28]Haishan Liu, Dejing Dou, Ruoming Jin, Paea LePendu, Nigam Shah:
Mining Biomedical Ontologies and Data Using RDF Hypergraphs. ICMLA (1) 2013: 141-146 - [c27]Rave Harpaz, William DuMouchel, Paea LePendu, Nigam H. Shah:
Empirical bayes model to combine signals of adverse drug reactions. KDD 2013: 1339-1347 - [c26]Graciela Gonzalez, Kevin Bretonnel Cohen, Casey S. Greene, Udo Hahn, Maricel G. Kann, Robert Leaman, Nigam Shah, Jieping Ye:
Session introduction. Pacific Symposium on Biocomputing 2013: 368-372 - [c25]Olivier Curé, Henri Maurer, Nigam Shah, Paea LePendu:
Refining Health Outcomes of Interest using Formal Concept Analysis and Semantic Query Expansion. SWAT4LS 2013 - 2012
- [j33]Udo Hahn, Kevin Bretonnel Cohen, Yael Garten, Nigam H. Shah:
Mining the pharmacogenomics literature - a survey of the state of the art. Briefings Bioinform. 13(4): 460-494 (2012) - [j32]Larisa N. Soldatova, Susanna-Assunta Sansone, Michel Dumontier, Nigam H. Shah:
Selected papers from the 14th Annual Bio-Ontologies Special Interest Group Meeting. J. Biomed. Semant. 3(S-1): I1 (2012) - [j31]Paea LePendu, Srinivasan V Iyer, Cédrick Fairon, Nigam H. Shah:
Annotation Analysis for Testing Drug Safety Signals using Unstructured Clinical Notes. J. Biomed. Semant. 3(S-1): S5 (2012) - [j30]Mark A. Musen, Natalya Fridman Noy, Nigam H. Shah, Patricia L. Whetzel, Christopher G. Chute, Margaret-Anne D. Storey, Barry Smith:
The National Center for Biomedical Ontology. J. Am. Medical Informatics Assoc. 19(2): 190-195 (2012) - [j29]Yi Liu, Adrien Coulet, Paea LePendu, Nigam H. Shah:
Using ontology-based annotation to profile disease research. J. Am. Medical Informatics Assoc. 19(e1) (2012) - [j28]Nigam H. Shah, Jessica D. Tenenbaum:
The coming age of data-driven medicine: translational bioinformatics' next frontier. J. Am. Medical Informatics Assoc. 19(e1) (2012) - [j27]Stephen T. Wu, Hongfang Liu, Dingcheng Li, Cui Tao, Mark A. Musen, Christopher G. Chute, Nigam H. Shah:
Unified Medical Language System term occurrences in clinical notes: a large-scale corpus analysis. J. Am. Medical Informatics Assoc. 19(e1) (2012) - [j26]Nigam H. Shah, Tyler Cole, Mark A. Musen:
Chapter 9: Analyses Using Disease Ontologies. PLoS Comput. Biol. 8(12) (2012) - [j25]Cameron Neylon, Jan Aerts, C. Titus Brown, Simon J. Coles, Les Hatton, Daniel Lemire, K. Jarrod Millman, Peter Murray-Rust, Fernando Pérez, Neil F. W. Saunders, Nigam Shah, Arfon M. Smith, Gaël Varoquaux, Egon L. Willighagen:
Changing computational research. The challenges ahead. Source Code Biol. Medicine 7: 2 (2012) - [c24]Byambajargal Byambajav, Tomasz Wiktor Wlodarczyk, Chunming Rong, Paea LePendu, Nigam Shah:
Performance of Left Outer Join on Hadoop with Right Side within Single Node Memory Size. AINA Workshops 2012: 1075-1080 - [c23]Kevin Bretonnel Cohen, Yael Garten, Nigam Shah, Udo Hahn:
Session introduction. Pacific Symposium on Biocomputing 2012: 375 - [e1]Alejandro Rodríguez González, Jyotishman Pathak, Mark D. Wilkinson, Nigam Shah, Robert Stevens, Richard D. Boyce, Ángel García-Crespo:
Proceedings of the Joint Workshop on Semantic Technologies Applied to Biomedical Informatics and Individualized Medicine, Boston, USA, November 12, 2012. CEUR Workshop Proceedings 930, CEUR-WS.org 2012 [contents] - 2011
- [j24]Syed Hamid Tirmizi, Stuart Aitken, Dilvan A. Moreira, Chris Mungall, Juan F. Sequeda, Nigam H. Shah, Daniel P. Miranker:
Mapping between the OBO and OWL ontology languages. J. Biomed. Semant. 2(S-1): S3 (2011) - [j23]Larisa N. Soldatova, Susanna-Assunta Sansone, Susie Stephens, Nigam H. Shah:
Selected papers from the 13th Annual Bio-Ontologies Special Interest Group Meeting. J. Biomed. Semant. 2(S-2): I1 (2011) - [j22]Adrien Coulet, Yael Garten, Michel Dumontier, Russ B. Altman, Mark A. Musen, Nigam H. Shah:
Integration and publication of heterogeneous text-mined relationships on the Semantic Web. J. Biomed. Semant. 2(S-2): S10 (2011) - [j21]Alison Callahan, Michel Dumontier, Nigam H. Shah:
HyQue: evaluating hypotheses using Semantic Web technologies. J. Biomed. Semant. 2(S-2): S3 (2011) - [j20]Atul J. Butte, Nigam H. Shah:
Computationally translating molecular discoveries into tools for medicine: translational bioinformatics articles now featured in JAMIA. J. Am. Medical Informatics Assoc. 18(4): 352-353 (2011) - [j19]Paea LePendu, Mark A. Musen, Nigam H. Shah:
Enabling enrichment analysis with the Human Disease Ontology. J. Biomed. Informatics 44(Supplement-1): S31-S38 (2011) - [j18]Patricia L. Whetzel, Natalya Fridman Noy, Nigam H. Shah, Paul R. Alexander, Csongor Nyulas, Tania Tudorache, Mark A. Musen:
BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications. Nucleic Acids Res. 39(Web-Server-Issue): 541-545 (2011) - [j17]Clément Jonquet, Paea LePendu, Sean M. Falconer, Adrien Coulet, Natalya Fridman Noy, Mark A. Musen, Nigam H. Shah:
NCBO Resource Index: Ontology-based search and mining of biomedical resources. J. Web Semant. 9(3): 316-324 (2011) - [c22]Cui Tao, Natalya Fridman Noy, Harold R. Solbrig, Nigam H. Shah, Mark A. Musen, Christopher G. Chute:
Proposed SKOS Extensions for BioPortal Terminology Services. JIST 2011: 342-349 - [c21]Paea LePendu, Mark A. Musen, Nigam H. Shah:
The Age of Data-Driven Medicine: Mining the Electronic Health Record. ICBO 2011 - [c20]Patricia L. Whetzel, Clément Jonquet, Cherie Youn, Michael Dorf, Ray W. Fergerson, Mark A. Musen, Nigam Shah:
The NCBO Annotator: Ontology-Based Annotation as a Web Service. ICBO 2011 - [c19]Patricia L. Whetzel, Natasha F. Noy, Nigam Shah, Paul R. Alexander, Michael Dorf, Ray W. Fergerson, Margaret-Anne D. Storey, Barry Smith, Christopher G. Chute, Mark A. Musen:
Bioportal: Ontologies and Integrated Data Resources at the Click of a Mouse. ICBO 2011 - [c18]Kevin Bretonnel Cohen, Yael Garten, Udo Hahn, Nigam H. Shah:
Workshop Introduction. Pacific Symposium on Biocomputing 2011: 362-363 - 2010
- [j16]Christophe Roeder, Clément Jonquet, Nigam H. Shah, William A. Baumgartner Jr., Karin Verspoor, Lawrence Hunter:
A UIMA wrapper for the NCBO annotator. Bioinform. 26(14): 1800-1801 (2010) - [j15]Larisa N. Soldatova, Phillip W. Lord, Susanna-Assunta Sansone, Susie Stephens, Nigam H. Shah:
Selected papers from the 12th annual Bio-Ontologies meeting. J. Biomed. Semant. 1(S-1): I1 (2010) - [j14]Clément Jonquet, Mark A. Musen, Nigam H. Shah:
Building a biomedical ontology recommender web service. J. Biomed. Semant. 1(S-1): S1 (2010) - [j13]Adrien Coulet, Nigam H. Shah, Yael Garten, Mark A. Musen, Russ B. Altman:
Using text to build semantic networks for pharmacogenomics. J. Biomed. Informatics 43(6): 1009-1019 (2010) - [c17]Clément Jonquet, Adrien Coulet, Nigam H. Shah, Mark A. Musen:
Indexation et intégration de ressources textuelles à l'aide d'ontologies : application au domaine biomédical. IC 2010: 271-282 - [c16]Adrien Coulet, Nigam H. Shah, Lawrence Hunter, Chitta Baral, Russ B. Altman:
Extraction of Genotype-Phenotype-Drug Relationships from Text: From Entity Recognition to Bioinformatics Application. Pacific Symposium on Biocomputing 2010: 485-487 - [c15]Paea LePendu, Natalya Fridman Noy, Clément Jonquet, Paul R. Alexander, Nigam H. Shah, Mark A. Musen:
Optimize First, Buy Later: Analyzing Metrics to Ramp-Up Very Large Knowledge Bases. ISWC (1) 2010: 486-501
2000 – 2009
- 2009
- [j12]Nigam H. Shah, Clément Jonquet, Annie P. Chiang, Atul J. Butte, Rong Chen, Mark A. Musen:
Ontology-driven indexing of public datasets for translational bioinformatics. BMC Bioinform. 10(S-2) (2009) - [j11]Nigam H. Shah, Nipun Bhatia, Clément Jonquet, Daniel L. Rubin, Annie P. Chiang, Mark A. Musen:
Comparison of concept recognizers for building the Open Biomedical Annotator. BMC Bioinform. 10(S-9): 14 (2009) - [j10]Natalya Fridman Noy, Nigam H. Shah, Patricia L. Whetzel, Benjamin Dai, Michael Dorf, Nicholas Griffith, Clément Jonquet, Daniel L. Rubin, Margaret-Anne D. Storey, Christopher G. Chute, Mark A. Musen:
BioPortal: ontologies and integrated data resources at the click of a mouse. Nucleic Acids Res. 37(Web-Server-Issue): 170-173 (2009) - [c14]Amir Ghazvinian, Natalya Fridman Noy, Clément Jonquet, Nigam H. Shah, Mark A. Musen:
What Four Million Mappings Can Tell You about Two Hundred Ontologies. ISWC 2009: 229-242 - [c13]Syed Hamid Tirmizi, Stuart Aitken, Dilvan A. Moreira, Chris Mungall, Juan F. Sequeda, Nigam H. Shah, Daniel P. Miranker:
OBO & OWL: Roundtrip Ontology Transformations. SWAT4LS 2009 - [p1]Nigam H. Shah, Mark A. Musen:
Ontologies for Formal Representation of Biological Systems. Handbook on Ontologies 2009: 445-461 - [r1]Nigam Shah:
Biomedical Data/Content Acquisition, Curation. Encyclopedia of Database Systems 2009: 224-229 - 2008
- [j9]Nikesh Kotecha, Kyle Bruck, William Lu, Nigam Shah:
Pathway knowledge base: An integrated pathway resource using BioPAX. Appl. Ontology 3(4): 235-245 (2008) - [j8]Daniel L. Rubin, Nigam Shah, Natalya Fridman Noy:
Biomedical ontologies: a functional perspective. Briefings Bioinform. 9(1): 75-90 (2008) - [j7]Robert J. Marinelli, Kelli Montgomery, Chih Long Liu, Nigam H. Shah, Wijan Prapong, Michael Nitzberg, Zachariah K. Zachariah, Gavin Sherlock, Yasodha Natkunam, Robert B. West, Matt van de Rijn, Patrick O. Brown, Catherine A. Ball:
The Stanford Tissue Microarray Database. Nucleic Acids Res. 36(Database-Issue): 871-877 (2008) - [c12]Wei-Nchih Lee, Nigam Shah, Karanjot Sundlass, Mark A. Musen:
Comparison of Ontology-based Semantic-Similarity Measures. AMIA 2008 - [c11]Nigam H. Shah, Mark A. Musen:
UMLS-Query: A Perl Module for Querying the UMLS. AMIA 2008 - [c10]Clément Jonquet, Mark A. Musen, Nigam Shah:
A System for Ontology-Based Annotation of Biomedical Data. DILS 2008: 144-152 - [c9]Natalya Fridman Noy, Nigam Shah, Benjamin Dai, Michael Dorf, Nicholas Griffith, Clément Jonquet, Michael Montegut, Daniel L. Rubin, Cherie Youn, Mark A. Musen:
BioPortal: A Web Repository for Biomedical Ontologies and Data Resources. ISWC (Posters & Demos) 2008 - 2007
- [j6]Balaji S. Srinivasan, Nigam H. Shah, Jason Flannick, Eduardo Abeliuk, Antal F. Novak, Serafim Batzoglou:
Current progress in network research: toward reference networks for key model organisms. Briefings Bioinform. 8(5): 318-332 (2007) - [j5]Nigam H. Shah, Daniel L. Rubin, Inigo Espinosa, Kelli Montgomery, Mark A. Musen:
Annotation and query of tissue microarray data using the NCI Thesaurus. BMC Bioinform. 8 (2007) - [c8]Dilvan A. Moreira, Nigam H. Shah, Mark A. Musen:
Interpretation Errors related to the GO Annotation File Format. AMIA 2007 - [c7]Woei-Jyh Lee, Louiqa Raschid, Padmini Srinivasan, Nigam Shah, Daniel L. Rubin, Natasha Fridman Noy:
Using Annotations from Controlled Vocabularies to Find Meaningful Associations. DILS 2007: 247-263 - [c6]Harith Alani, Natasha Fridman Noy, Nigam Shah, Nigel Shadbolt, Mark A. Musen:
Searching ontologies based on content: experiments in the biomedical domain. K-CAP 2007: 55-62 - 2006
- [j4]Stephen A. Racunas, Nigam Shah, Nina V. Fedoroff:
A case study in pathway knowledgebase verification. BMC Bioinform. 7: 196 (2006) - [c5]Nigam H. Shah, Daniel L. Rubin, Kaustubh S. Supekar, Mark A. Musen:
Ontology-based Annotation and Query of Tissue Microarray Data. AMIA 2006 - 2004
- [j3]N. H. Shah, Nina V. Fedoroff:
CLENCH: a program for calculating Cluster ENriCHment using the Gene Ontology. Bioinform. 20(7): 1196-1197 (2004) - [c4]Stephen A. Racunas, Christopher Griffin, Nigam Shah:
A Finite Model Theory for Biological Hypotheses. CSB 2004: 616-620 - [c3]Stephen A. Racunas, N. H. Shah, István Albert, Nina V. Fedoroff:
HyBrow: a prototype system for computer-aided hypothesis evaluation. ISMB/ECCB (Supplement of Bioinformatics) 2004: 257-264 - 2003
- [j2]N. H. Shah, D. C. King, P. N. Shah, Nina V. Fedoroff:
A tool-kit for cDNA microarray and promoter analysis. Bioinform. 19(14): 1846-1848 (2003) - [c2]Nigam Shah, Jorge Lepre, Yuhai Tu, Gustavo Stolovitzky:
Can We Identify Cellular Pathways Implicated in Cancer Using Gene Expression Data? CSB 2003: 94-103 - [c1]Steve Racunas, Nigam Shah, Nina V. Fedoroff:
A Contradiction-Based Framework for Testing Gene Regulation Hypotheses. CSB 2003: 634-638
1990 – 1999
- 1996
- [j1]Wen-Ben Jone, Nigam Shah, Anita Gleason, Sunil R. Das:
PGEN: A Novel Approach to Sequential Circuit Test Generation. VLSI Design 4(3): 149-165 (1996)
Coauthor Index
Scott L. Fleming
aka: Scott Lanyon Fleming
aka: Scott Lanyon Fleming
Jason Alan Fries
aka: Jason A. Fries
aka: Jason A. Fries
Stephen Pfohl
aka: Stephen R. Pfohl
aka: Stephen R. Pfohl
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