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2020 – today
- 2024
[j29]Christian Rose
, Jonathan H. Chen:
Learning from the EHR to implement AI in healthcare. npj Digit. Medicine 7(1) (2024)- [j28]Thomas Savage, Ashwin Nayak, Robert Gallo, Ekanath Rangan, Jonathan H. Chen:
Diagnostic reasoning prompts reveal the potential for large language model interpretability in medicine. npj Digit. Medicine 7(1) (2024) - [c30]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 - [i11]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) - [i10]Yixing Jiang, Jeremy Irvin, Ji Hun Wang, Muhammad Ahmed Chaudhry, Jonathan H. Chen, Andrew Y. Ng:
Many-Shot In-Context Learning in Multimodal Foundation Models. CoRR abs/2405.09798 (2024) - [i9]Pooya Ashtari, Pourya Behmandpoor, Fateme Nateghi Haredasht, Jonathan H. Chen, Panagiotis Patrinos, Sabine Van Huffel:
Quantization-free Lossy Image Compression Using Integer Matrix Factorization. CoRR abs/2408.12691 (2024) - [i8]Thomas Savage, Stephen Ma, Abdessalem Boukil, Vishwesh Patel, Ekanath Rangan, Ivan Rodriguez, Jonathan H. Chen:
Fine Tuning Large Language Models for Medicine: The Role and Importance of Direct Preference Optimization. CoRR abs/2409.12741 (2024) - 2023
- [j27]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) - [j26]Akshay Swaminathan, Iván López, William Wang, Ujwal Srivastava, Edward Tran, Aarohi Bhargava-Shah, Janet Y. Wu, Alexander L. Ren, Kaitlin Caoili, Brandon Bui, Layth Alkhani, Susan Lee, Nathan Mohit, Noel Seo, Nicholas Macedo, Winson Cheng, Charles Liu, Reena Thomas, Jonathan H. Chen, Olivier Gevaert:
Selective prediction for extracting unstructured clinical data. J. Am. Medical Informatics Assoc. 31(1): 188-197 (2023) - [j25]Sajjad Fouladvand, Federico Reyes Gomez, Hamed Nilforoshan, Matthew Schwede, Morteza Noshad, Olivia Jee, Jiaxuan You, Rok Sosic, Jure Leskovec, Jonathan H. Chen:
Graph-based clinical recommender: Predicting specialists procedure orders using graph representation learning. J. Biomed. Informatics 143: 104407 (2023) - [j24]Nandita Bhaskhar, Wui Ip, Jonathan H. Chen, Daniel L. Rubin:
Clinical outcome prediction using observational supervision with electronic health records and audit logs. J. Biomed. Informatics 147: 104522 (2023) - [j23]Akshay Swaminathan, Iván López, Rafael Antonio Garcia Mar, Tyler Heist, Tom McClintock, Kaitlin Caoili, Madeline Grace, Matthew Rubashkin, Michael N. Boggs, Jonathan H. Chen, Olivier Gevaert, David Mou, Matthew K. Nock:
Natural language processing system for rapid detection and intervention of mental health crisis chat messages. npj Digit. Medicine 6 (2023) - [i7]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) - [i6]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) - [i5]Thomas Savage, Ashwin Nayak, Robert Gallo, Ekanath Rangan, Jonathan H. Chen:
Diagnostic Reasoning Prompts Reveal the Potential for Large Language Model Interpretability in Medicine. CoRR abs/2308.06834 (2023) - [i4]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) - 2022
- [j22]Vy T. Ho, Rachael C. Aikens, Geoffrey J. Tso, Paul A. Heidenreich, Christopher D. Sharp, Steven M. Asch, Jonathan H. Chen, Neil K. Shah:
Interruptive Electronic Alerts for Choosing Wisely Recommendations: A Cluster Randomized Controlled Trial. J. Am. Medical Informatics Assoc. 29(11): 1941-1948 (2022) - [j21]Christian Rose, Robert Thombley, Morteza Noshad, Yun Lu, Heather A Clancy, David Schlessinger, Ron C. Li, Vincent X. Liu, Jonathan H. Chen, Julia Adler-Milstein:
Team is brain: leveraging EHR audit log data for new insights into acute care processes. J. Am. Medical Informatics Assoc. 30(1): 8-15 (2022) - [j20]Morteza Noshad, Christian Rose, Jonathan H. Chen:
Signal from the noise: A mixed graphical and quantitative process mining approach to evaluate care pathways applied to emergency stroke care. J. Biomed. Informatics 127: 104004 (2022) - [c29]Conor K. Corbin, Michael Baiocchi, Jonathan H. Chen:
How to Avoid Incorrect Clinical Machine Learning Model Performance Estimates When Class Labels Are Only Partially Observed. AMIA 2022 - [c28]Kush Gupta, Jason Hom, Ted Ross, Jonathan Masterson, Alexander Chin, Arnold Milstein, Jonathan H. Chen:
Modifiable Inpatient Cost Variability at a Large Academic Medical Center. AMIA 2022 - [c27]Samson Peter, Maggie Wang, Chi D. Chu, Delphine S. Tuot, Arhana Chattopadhyay, Jonathan H. Chen:
Gaps in Nephrology Referral Care Utilization in Patients at High-Risk of Progression to Kidney Failure. AMIA 2022 - [c26]Christian Rose, Robert Thombley, Morteza Noshad, Ron Li, Wendy Lu, Heather A Clancy, David Schlessinger, Vincent X. Liu, Jonathan H. Chen, Julia Adler-Milstein:
Leveraging EHR Audit Log Data to Unlock New Insights into Care Processes and Outcomes. AMIA 2022 - [i3]David Ouyang, John Theurer, Nathan R. Stein, J. Weston Hughes, Pierre Elias, Bryan He, Neal Yuan, Grant Duffy, Roopinder K. Sandhu, Joseph Ebinger, Patrick Botting, Melvin Jujjavarapu, Brian Claggett, James E. Tooley, Tim Poterucha, Jonathan H. Chen, Michael Nurok, Marco V. Perez, Adler J. Perotte, James Y. Zou, Nancy R. Cook, Sumeet S. Chugh, Susan Cheng, Christine M. Albert:
Electrocardiographic Deep Learning for Predicting Post-Procedural Mortality. CoRR abs/2205.03242 (2022) - [i2]Conor K. Corbin, Michael Baiocchi, Jonathan H. Chen:
Avoiding Biased Clinical Machine Learning Model Performance Estimates in the Presence of Label Selection. CoRR abs/2209.09188 (2022) - 2021
- [j19]Jared A. Shenson, Ivana Jankovic, Hyo Jung Hong, Benjamin Weia, Lee White, Jonathan H. Chen, Matthew Eisenberg:
Engaging Housestaff as Informatics Collaborators: Educational and Operational Opportunities. Appl. Clin. Inform. 12(5): 1150-1156 (2021) - [j18]Minh Nguyen, Ivana Jankovic, Laurynas Kalesinskas, Michael T. M. Baiocchi, Jonathan H. Chen:
Machine learning for initial insulin estimation in hospitalized patients. J. Am. Medical Informatics Assoc. 28(10): 2212-2219 (2021) - [j17]Minh Nguyen, Conor K. Corbin, Tiffany Eulalio, Nicolai P. Ostberg, Gautam Machiraju, Ben J. Marafino, Michael Baiocchi, Christian Rose, Jonathan H. Chen:
Developing machine learning models to personalize care levels among emergency room patients for hospital admission. J. Am. Medical Informatics Assoc. 28(11): 2423-2432 (2021) - [j16]Rachael C. Aikens, Joseph Rigdon, Justin Lee, Michael T. M. Baiocchi, Andrew B. Goldstone, Peter Chiu, Y. Joseph Woo, Jonathan H. Chen:
stratamatch: Prognostic Score Stratification Using a Pilot Design. R J. 13(1): 614 (2021) - [c25]Conor K. Corbin, Arhana Chattopadhyah, Lillian Sung, Amy Chang, Stan Deresinski, Jonathan H. Chen:
A Retrospective Analysis of Machine Learning Driven Antibiotic Selection in the Emergency Department. AMIA 2021 - [c24]Wui Ip, Priya Prahalad, Jonathan Palma, Jonathan H. Chen:
A Data-Driven Algorithm to Recommend Initial Clinical Workup for Outpatient Specialty Referral. AMIA 2021 - [c23]Grace Y. E. Kim, Morteza Noshad, Henning Stehr, Rebecca Rojansky, Dita Gratzinger, Jean Oak, Rondeep Brar, David Iberri, Christina Kong, James L. Zehnder, Jonathan H. Chen:
Machine Learning Predictability of Clinical Next Generation Sequencing for Hematologic Malignancies to Guide High-Value Precision Medicine. AMIA 2021 - [c22]Andre Kumar, Rachael C. Aikens, Jason Horn, Lisa Shieh, Mark A. Musen, Michael Baiocchi, Russ B. Altman, Mary K. Goldstein, Steven M. Asch, Jonathan H. Chen:
Randomized user testing of recommender system clinical decision support. AMIA 2021 - [c21]Minh Nguyen, Nicolai P. Ostberg, Conor K. Corbin, Tiffany Eulalio, Gautam Machiraju, Ben J. Marafino, Michael Baiocchi, Christian Rose, Jonathan H. Chen:
Predicting Level of Care for Emergency Hospital Admissions to Optimize Triage. AMIA 2021 - [c20]Christian Rose, Morteza Noshad, Jonathan H. Chen:
Signal from the Noise: Quantitative Measures of Conformity and Variability From Process Mining Maps. AMIA 2021 - [c19]Olga Afanasiev, Joanne Berghout, Steven E. Brenner, Martha L. Bulyk, Dana C. Crawford, Jonathan H. Chen, Roxana Daneshjou, Lukasz Kidzinski:
Computational Challenges and Artificial Intelligence in Precision Medicine. PSB 2021 - 2020
- [j15]Seyedeh Neelufar Payrovnaziri, Zhaoyi Chen, Pablo Rengifo-Moreno, Tim Miller, Jiang Bian, Jonathan H. Chen, Xiuwen Liu, Zhe He:
Explainable artificial intelligence models using real-world electronic health record data: a systematic scoping review. J. Am. Medical Informatics Assoc. 27(7): 1173-1185 (2020) - [j14]Andre Kumar, Rachael C. Aikens, Jason Hom, Lisa Shieh, Jonathan Chiang, David Morales, Divya Saini, Mark A. Musen, Michael T. M. Baiocchi, Russ B. Altman, Mary K. Goldstein, Steven M. Asch, Jonathan H. Chen:
OrderRex clinical user testing: a randomized trial of recommender system decision support on simulated cases. J. Am. Medical Informatics Assoc. 27(12): 1850-1859 (2020) - [j13]Amirata Ghorbani, David Ouyang, Abubakar Abid, Bryan He, Jonathan H. Chen, Robert A. Harrington, David H. Liang, Euan A. Ashley, James Y. Zou:
Deep learning interpretation of echocardiograms. npj Digit. Medicine 3 (2020) - [c18]Ron C. Li, Naveen Muthu, Margaret Smith, Swaminathan Kandaswamy, Jonathan H. Chen:
It's not just a last mile problem: Partnering with process improvement and human factors to integrate machine learning into healthcare delivery. AMIA 2020 - [c17]Morteza Noshad, Christian Rose, Robert Thombley, Jonathan Chiang, Conor K. Corbin, Minh Nguyen, Vincent X. Liu, Julia Adler-Milstein, Jonathan H. Chen:
Context is Key: Using the Audit Log to Capture Contextual Factors Affecting Stroke Care Processes. AMIA 2020 - [c16]Yiye Zhang, Jonathan H. Chen, Adam Wright, Jessica S. Ancker, Marc Tobias:
Data-Driven Clinical Decision Support for Computerized Physician Order Entry: Development, Evaluation, and Implementation. AMIA 2020 - [c15]Roxana Daneshjou, Lukasz Kidzinski, Olga Afanasiev, Jonathan H. Chen:
Session Introduction. PSB 2020: 1-6 - [i1]Morteza Noshad, Ivana Jankovic, Jonathan H. Chen:
Clinical Recommender System: Predicting Medical Specialty Diagnostic Choices with Neural Network Ensembles. CoRR abs/2007.12161 (2020)
2010 – 2019
- 2019
- [j12]Alison E. Fohner, John D. Greene, Brian L. Lawson, Jonathan H. Chen, Patricia Kipnis, Gabriel J. Escobar, Vincent X. Liu:
Assessing clinical heterogeneity in sepsis through treatment patterns and machine learning. J. Am. Medical Informatics Assoc. 26(12): 1466-1477 (2019) - [c14]Ron C. Li, Imon Banerjee, Daniel L. Rubin, Jonathan H. Chen:
Detecting unanticipated actions downstream from clinical decision support: a data mining approach. AMIA 2019 - [c13]Song Xu, Jason Horn, Santhosh Balasubramanian, Lee F. Schroeder, Nader Najafi, Shivaal Roy, Jonathan H. Chen:
Prevalence and Predictability of Low Yield Inpatient Laboratory Diagnostic Tests. AMIA 2019 - 2018
- [j11]Ron C. Li, Trit Garg, Tony Cun, Lisa Shieh, Gomathi Krishnan, Daniel Z. Fang, Jonathan H. Chen:
Impact of problem-based charting on the utilization and accuracy of the electronic problem list. J. Am. Medical Informatics Assoc. 25(5): 548-554 (2018) - [j10]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) - [c12]Santhosh Balasubramanian, Jason Hom, Shivaal Roy, Jonathan H. Chen:
Machine Learning Predictable Inpatient Lab Results for High-Value Care. AMIA 2018 - [c11]Ron C. Li, Jason K. Wang, Christopher D. Sharp, Jonathan H. Chen:
A "bottom up" data driven approach to curating electronic order sets. AMIA 2018 - 2017
- [j9]Jonathan H. Chen, Muthuraman Alagappan, Mary K. Goldstein, Steven M. Asch, Russ B. Altman:
Decaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets. Int. J. Medical Informatics 102: 71-79 (2017) - [j8]Jonathan H. Chen, Mary K. Goldstein, Steven M. Asch, Lester W. Mackey, Russ B. Altman:
Predicting inpatient clinical order patterns with probabilistic topic models vs conventional order sets. J. Am. Medical Informatics Assoc. 24(3): 472-480 (2017) - [c10]Jason K. Wang, Alejandro Schuler, Nigam Shah, Jonathan H. Chen:
Impact of Clinician Experience on Machine Learned Clinical Order Patterns. AMIA 2017 - [c9]Muthuraman Alagappan, Mary K. Goldstein, Steven M. Asch, Russ B. Altman, Jonathan H. Chen:
Decaying Relevance of Clinical Data when Predicting Future Decisions. CRI 2017 - [c8]Ron C. Li, Lisa Shieh, Gomathi Krishnan, Daniel Z. Fang, Jonathan H. Chen:
Problem based charting: a method for improving problem list utilization and completeness. CRI 2017 - [c7]Tiffany I. Leung, Mary K. Goldstein, Mark A. Musen, Ruth Cronkite, Jonathan H. Chen, Assaf Gottlieb, Eran Leitersdorf:
The New HIT: Human Health Information Technology. MedInfo 2017: 768-772 - [c6]Lana X. Garmire, Stephen V. Gliske, Quynh C. Nguyen, Jonathan H. Chen, Shamim Nemati, John D. Van Horn, Jason H. Moore, Carol Shreffler, Michelle Dunn:
The Training of Next Generation Data Scientists in Biomedicine. PSB 2017: 640-645 - 2016
- [j7]Jonathan H. Chen, Tanya Podchiyska, Russ B. Altman:
OrderRex: clinical order decision support and outcome predictions by data-mining electronic medical records. J. Am. Medical Informatics Assoc. 23(2): 339-348 (2016) - [c5]Jonathan H. Chen, Mary K. Goldstein, Steven M. Asch, Russ B. Altman:
Usability of an Automated Recommender System for Clinical Order Entry. AMIA 2016 - [c4]Jonathan H. Chen, Mary K. Goldstein, Steven M. Asch, Lester W. Mackey, Russ B. Altman:
Automated Organization of Electronic Health Record Data by Probabilistic Topic Modeling to Inform Clinical Decision Making. CRI 2016 - [c3]Jonathan H. Chen, Mary K. Goldstein, Steven M. Asch, Russ B. Altman:
Dynamically Evolving Clinical Practices and Implications for Predicting Medical Decisions. PSB 2016: 195-206 - 2014
- [c2]Jonathan H. Chen, Russ B. Altman:
"Doctors who ordered this also ordered..." Automated physician order recommendations and outcome predictions by data-mining electronic medical records. AMIA 2014 - 2011
- [j6]Matthew A. Kayala, Chloé-Agathe Azencott, Jonathan H. Chen, Pierre Baldi:
Learning to Predict Chemical Reactions. J. Chem. Inf. Model. 51(9): 2209-2222 (2011)
2000 – 2009
- 2009
- [j5]Jonathan H. Chen, Pierre Baldi:
No Electron Left Behind: A Rule-Based Expert System To Predict Chemical Reactions and Reaction Mechanisms. J. Chem. Inf. Model. 49(9): 2034-2043 (2009) - 2007
- [j4]Jonathan H. Chen, Erik Linstead, Sanjay Joshua Swamidass, Dennis Wang, Pierre Baldi:
ChemDB update - full-text search and virtual chemical space. Bioinform. 23(17): 2348-2351 (2007) - [j3]Chloé-Agathe Azencott, Alexandre Ksikes, S. Joshua Swamidass, Jonathan H. Chen, Liva Ralaivola, Pierre Baldi:
One- to Four-Dimensional Kernels for Virtual Screening and the Prediction of Physical, Chemical, and Biological Properties. J. Chem. Inf. Model. 47(3): 965-974 (2007) - 2006
- [j2]Samuel A. Danziger, Sanjay Joshua Swamidass, Jue Zeng, Lawrence R. Dearth, Qiang Lu, Jonathan H. Chen, Jianlin Cheng, Vinh P. Hoang, Hiroto Saigo, Ray Luo, Pierre Baldi, Rainer K. Brachmann, Richard H. Lathrop:
Functional Census of Mutation Sequence Spaces: The Example of p53 Cancer Rescue Mutants. IEEE ACM Trans. Comput. Biol. Bioinform. 3(2): 114-125 (2006) - 2005
- [j1]Jonathan H. Chen, Sanjay Joshua Swamidass, Yimeng Dou, Jocelyne Bruand, Pierre Baldi:
ChemDB: a public database of small molecules and related chemoinformatics resources. Bioinform. 21(22): 4133-4139 (2005) - [c1]Sanjay Joshua Swamidass, Jonathan H. Chen, Jocelyne Bruand, Peter Phung, Liva Ralaivola, Pierre Baldi:
Kernels for small molecules and the prediction of mutagenicity, toxicity and anti-cancer activity. ISMB (Supplement of Bioinformatics) 2005: 359-368
Coauthor Index
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