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Akshay Chaudhari
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2020 – today
- 2024
- [c19]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 - [i27]Zhihong Chen, Maya Varma, Jean-Benoit Delbrouck, Magdalini Paschali, Louis Blankemeier, Dave Van Veen, Jeya Maria Jose Valanarasu, Alaa Youssef, Joseph Paul Cohen, Eduardo Pontes Reis, Emily Bao Tsai, Andrew Johnston, Cameron Olsen, Tanishq Mathew Abraham, Sergios Gatidis, Akshay S. Chaudhari, Curtis P. Langlotz:
CheXagent: Towards a Foundation Model for Chest X-Ray Interpretation. CoRR abs/2401.12208 (2024) - [i26]Asad Aali, Dave Van Veen, Yamin Ishraq Arefeen, Jason Hom, Christian Bluethgen, Eduardo Pontes Reis, Sergios Gatidis, Namuun Clifford, Joseph Daws, Arash S. Tehrani, Jangwon Kim, Akshay S. Chaudhari:
A Benchmark of Domain-Adapted Large Language Models for Generating Brief Hospital Course Summaries. CoRR abs/2403.05720 (2024) - 2023
- [j10]Peyman Shokrollahi, Juan Manuel Zambrano Chaves, Jonathan P. H. Lam, Avishkar Sharma, Debashish Pal, Naeim Bahrami, Akshay S. Chaudhari, Andreas M. Loening:
Radiology Decision Support System for Selecting Appropriate CT Imaging Titles Using Machine Learning Techniques Based on Electronic Medical Records. IEEE Access 11: 99222-99236 (2023) - [j9]Darren Wei Wen Low, Akshay Chaudhari, Dharmesh Kumar, A. Senthil Kumar:
Convolutional neural networks for prediction of geometrical errors in incremental sheet metal forming. J. Intell. Manuf. 34(5): 2373-2386 (2023) - [j8]Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Anna Wuest, Sarthak Pati, Hasan Kassem, Maximilian Zenk, Ujjwal Baid, Prakash Narayana Moorthy, Alexander Chowdhury, Junyi Guo, Sahil S. Nalawade, Jacob Rosenthal, David Kanter, Maria Xenochristou, Daniel J. Beutel, Verena Chung, Timothy Bergquist, James A. Eddy, Abubakar Abid, Lewis Tunstall, Omar Sanseviero, Dimitrios Dimitriadis, Yiming Qian, Xinxing Xu, Yong Liu, Rick Siow Mong Goh, Srini Bala, Victor Bittorf, Sreekar Reddy Puchala, Biagio Ricciuti, Soujanya Samineni, Eshna Sengupta, Akshay Chaudhari, Cody Coleman, Bala Desinghu, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Xinyuan Huang, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Cassiano Ferro Moraes, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Abhishek Singh, Jayaraman J. Thiagarajan, Jacob Albrecht, Thomas Wolf, Geralyn Miller, Huazhu Fu, Prashant Shah, Daguang Xu, Poonam Yadav, David Talby, Mark M. Awad, Jeremy P. Howard, Michael Rosenthal, Luigi Marchionni, Massimo Loda, Jason M. Johnson, Spyridon Bakas, Peter Mattson:
Federated benchmarking of medical artificial intelligence with MedPerf. Nat. Mac. Intell. 5(7): 799-810 (2023) - [j7]Tian Tan, Anthony A. Gatti, Bingfei Fan, Kevin G. Shea, Seth L. Sherman, Scott D. Uhlrich, Jennifer L. Hicks, Scott L. Delp, Peter B. Shull, Akshay S. Chaudhari:
A scoping review of portable sensing for out-of-lab anterior cruciate ligament injury prevention and rehabilitation. npj Digit. Medicine 6 (2023) - [j6]Shih-Cheng Huang, Anuj Pareek, Malte Jensen, Matthew P. Lungren, Serena Yeung, Akshay S. Chaudhari:
Self-supervised learning for medical image classification: a systematic review and implementation guidelines. npj Digit. Medicine 6 (2023) - [j5]Scott D. Uhlrich, Antoine Falisse, Lukasz Kidzinski, Julie Muccini, Michael Ko, Akshay S. Chaudhari, Jennifer L. Hicks, Scott L. Delp:
OpenCap: Human movement dynamics from smartphone videos. PLoS Comput. Biol. 19(10) (2023) - [c18]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 - [c17]Louis Blankemeier, Theodore Zhao, Robert Tinn, Sid Kiblawi, Yu Gu, Akshay Chaudhari, Hoifung Poon, Sheng Zhang, Mu Wei, Joseph Preston:
Interactive Span Recommendation for Biomedical Text. ClinicalNLP@ACL 2023: 373-384 - [c16]Dave Van Veen, Cara Van Uden, Maayane Attias, Anuj Pareek, Christian Bluethgen, Malgorzata Polacin, Wah Chiu, Jean-Benoit Delbrouck, Juan Manuel Zambrano Chaves, Curtis P. Langlotz, Akshay Chaudhari, John M. Pauly:
RadAdapt: Radiology Report Summarization via Lightweight Domain Adaptation of Large Language Models. BioNLP@ACL 2023: 449-460 - [c15]Maya Varma, Jean-Benoit Delbrouck, Sarah M. Hooper, Akshay Chaudhari, Curtis P. Langlotz:
ViLLA: Fine-Grained Vision-Language Representation Learning from Real-World Data. ICCV 2023: 22168-22178 - [c14]Tiange Xiang, Mahmut Yurt, Ali B. Syed, Kawin Setsompop, Akshay Chaudhari:
DDM2: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models. ICLR 2023 - [c13]Rogier van der Sluijs, Nandita Bhaskhar, Daniel L. Rubin, Curtis P. Langlotz, Akshay S. Chaudhari:
Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays. MIDL 2023: 444-467 - [c12]Juanma Zambrano Chaves, Nandita Bhaskhar, Maayane Attias, Jean-Benoit Delbrouck, Daniel L. Rubin, Andreas M. Loening, Curtis P. Langlotz, Akshay Chaudhari:
RaLEs: a Benchmark for Radiology Language Evaluations. NeurIPS 2023 - [i25]Rogier van der Sluijs, Nandita Bhaskhar, Daniel L. Rubin, Curtis P. Langlotz, Akshay Chaudhari:
Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays. CoRR abs/2301.12636 (2023) - [i24]Tiange Xiang, Mahmut Yurt, Ali B. Syed, Kawin Setsompop, Akshay Chaudhari:
DDM2: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models. CoRR abs/2302.03018 (2023) - [i23]Louis Blankemeier, Arjun D. Desai, Juan Manuel Zambrano Chaves, Andrew Wentland, Sally Yao, Eduardo Pontes Reis, Malte Jensen, Bhanushree Bahl, Khushboo Arora, Bhavik N. Patel, Leon Lenchik, Marc H. Willis, Robert D. Boutin, Akshay S. Chaudhari:
Comp2Comp: Open-Source Body Composition Assessment on Computed Tomography. CoRR abs/2302.06568 (2023) - [i22]Joseph Paul Cohen, Rupert Brooks, Sovann En, Evan Zucker, Anuj Pareek, Matthew P. Lungren, Akshay Chaudhari:
The Effect of Counterfactuals on Reading Chest X-rays. CoRR abs/2304.00487 (2023) - [i21]Dave Van Veen, Cara Van Uden, Maayane Attias, Anuj Pareek, Christian Bluethgen, Malgorzata Polacin, Wah Chiu, Jean-Benoit Delbrouck, Juan Manuel Zambrano Chaves, Curtis P. Langlotz, Akshay S. Chaudhari, John M. Pauly:
RadAdapt: Radiology Report Summarization via Lightweight Domain Adaptation of Large Language Models. CoRR abs/2305.01146 (2023) - [i20]Maya Varma, Jean-Benoit Delbrouck, Sarah M. Hooper, Akshay Chaudhari, Curtis P. Langlotz:
ViLLA: Fine-Grained Vision-Language Representation Learning from Real-World Data. CoRR abs/2308.11194 (2023) - [i19]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) - [i18]Dave Van Veen, Cara Van Uden, Louis Blankemeier, Jean-Benoit Delbrouck, Asad Aali, Christian Bluethgen, Anuj Pareek, Malgorzata Polacin, William Collins, Neera Ahuja, Curtis P. Langlotz, Jason Hom, Sergios Gatidis, John M. Pauly, Akshay S. Chaudhari:
Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts. CoRR abs/2309.07430 (2023) - [i17]Joseph Paul Cohen, Louis Blankemeier, Akshay Chaudhari:
Identifying Spurious Correlations using Counterfactual Alignment. CoRR abs/2312.02186 (2023) - 2022
- [j4]Sayim Gokyar, Fraser J. L. Robb, Wolfgang Kainz, Akshay Chaudhari, Simone Angela Winkler:
Correction to "MRSaiFE: An AI-Based Approach Toward the Real-Time Prediction of Specific Absorption Rate". IEEE Access 10: 19925 (2022) - [c11]Jean-Benoit Delbrouck, Khaled Saab, Maya Varma, Sabri Eyuboglu, Pierre J. Chambon, Jared Dunnmon, Juan Zambrano, Akshay Chaudhari, Curtis P. Langlotz:
ViLMedic: a framework for research at the intersection of vision and language in medical AI. ACL (demo) 2022: 23-34 - [c10]Louis Blankemeier, Isabel Gallegos, Juan Manuel Zambrano Chaves, David J. Maron, Alexander T. Sandhu, Fátima Rodriguez, Daniel L. Rubin, Bhavik N. Patel, Marc H. Willis, Robert D. Boutin, Akshay S. Chaudhari:
Opportunistic Incidence Prediction of Multiple Chronic Diseases from Abdominal CT Imaging Using Multi-task Learning. MICCAI (8) 2022: 309-318 - [c9]Beliz Gunel, Arda Sahiner, Arjun D. Desai, Akshay S. Chaudhari, Shreyas Vasanawala, Mert Pilanci, John M. Pauly:
Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction. MICCAI (6) 2022: 737-747 - [c8]Joseph Paul Cohen, Joseph D. Viviano, Paul Bertin, Paul Morrison, Parsa Torabian, Matteo Guarrera, Matthew P. Lungren, Akshay Chaudhari, Rupert Brooks, Mohammad Hashir, Hadrien Bertrand:
TorchXRayVision: A library of chest X-ray datasets and models. MIDL 2022: 231-249 - [c7]Arjun D. Desai, Beliz Gunel, Batu M. Ozturkler, Harris Beg, Shreyas Vasanawala, Brian A. Hargreaves, Christopher Ré, John M. Pauly, Akshay S. Chaudhari:
VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI Reconstruction. MIDL 2022: 325-352 - [i16]Arjun D. Desai, Andrew M. Schmidt, Elka B. Rubin, Christopher M. Sandino, Marianne S. Black, Valentina Mazzoli, Kathryn J. Stevens, Robert Boutin, Christopher Ré, Garry Gold, Brian A. Hargreaves, Akshay S. Chaudhari:
SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation. CoRR abs/2203.06823 (2022) - [i15]Beliz Gunel, Arda Sahiner, Arjun D. Desai, Akshay S. Chaudhari, Shreyas Vasanawala, Mert Pilanci, John M. Pauly:
Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction. CoRR abs/2204.10436 (2022) - [i14]Pierre J. Chambon, Christian Bluethgen, Curtis P. Langlotz, Akshay Chaudhari:
Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains. CoRR abs/2210.04133 (2022) - [i13]Jeffrey Dominic, Nandita Bhaskhar, Arjun D. Desai, Andrew M. Schmidt, Elka B. Rubin, Beliz Gunel, Garry E. Gold, Brian A. Hargreaves, Leon Lenchik, Robert Boutin, Akshay S. Chaudhari:
Data-Limited Tissue Segmentation using Inpainting-Based Self-Supervised Learning. CoRR abs/2210.07936 (2022) - [i12]Dave Van Veen, Rogier van der Sluijs, Batu Ozturkler, Arjun D. Desai, Christian Bluethgen, Robert D. Boutin, Marc H. Willis, Gordon Wetzstein, David B. Lindell, Shreyas Vasanawala, John M. Pauly, Akshay S. Chaudhari:
Scale-Agnostic Super-Resolution in MRI using Feature-Based Coordinate Networks. CoRR abs/2210.08676 (2022) - [i11]Pierre J. Chambon, Christian Bluethgen, Jean-Benoit Delbrouck, Rogier van der Sluijs, Malgorzata Polacin, Juan Manuel Zambrano Chaves, Tanishq Mathew Abraham, Shivanshu Purohit, Curtis P. Langlotz, Akshay Chaudhari:
RoentGen: Vision-Language Foundation Model for Chest X-ray Generation. CoRR abs/2211.12737 (2022) - 2021
- [j3]Sayim Gokyar, Fraser J. L. Robb, Wolfgang Kainz, Akshay Chaudhari, Simone Angela Winkler:
MRSaiFE: An AI-Based Approach Towards the Real-Time Prediction of Specific Absorption Rate. IEEE Access 9: 140824-140834 (2021) - [j2]Akshay S. Chaudhari, Erik Mittra, Guido A. Davidzon, Praveen Gulaka, Harsh Gandhi, Adam Brown, Tao Zhang, Shyam Srinivas, Enhao Gong, Greg Zaharchuk, Hossein Jadvar:
Author Correction: Low-count whole-body PET with deep learning in a multicenter and externally validated study. npj Digit. Medicine 4 (2021) - [j1]Akshay S. Chaudhari, Erik Mittra, Guido A. Davidzon, Praveen Gulaka, Harsh Gandhi, Adam Brown, Tao Zhang, Shyam Srinivas, Enhao Gong, Greg Zaharchuk, Hossein Jadvar:
Low-count whole-body PET with deep learning in a multicenter and externally validated study. npj Digit. Medicine 4 (2021) - [c6]Adrit Rao, Akshay Chaudhari, Oliver Aalami:
Development of the Next Generation Hand-Held Doppler with Waveform Phasicity Predictive Capabilities Using Deep Learning. CLIP/DCL/LL-COVID19/PPML@MICCAI 2021: 56-67 - [c5]Mohammad Zalbagi Darestani, Akshay S. Chaudhari, Reinhard Heckel:
Measuring Robustness in Deep Learning Based Compressive Sensing. ICML 2021: 2433-2444 - [c4]Joseph Paul Cohen, Rupert Brooks, Sovann En, Evan Zucker, Anuj Pareek, Matthew P. Lungren, Akshay Chaudhari:
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays. MIDL 2021: 74-104 - [c3]Arjun D. Desai, Andrew M. Schmidt, Elka B. Rubin, Christopher M. Sandino, Marianne S. Black, Valentina Mazzoli, Kathryn J. Stevens, Robert Boutin, Christopher Ré, Garry Gold, Brian A. Hargreaves, Akshay Chaudhari:
SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation. NeurIPS Datasets and Benchmarks 2021 - [c2]Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jia Liang, Akshay Chaudhari, Andreas Spanias:
Designing Counterfactual Generators using Deep Model Inversion. NeurIPS 2021: 16873-16884 - [i10]Joseph Paul Cohen, Rupert Brooks, Sovann En, Evan Zucker, Anuj Pareek, Matthew P. Lungren, Akshay Chaudhari:
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Progressive Exaggeration on Chest X-rays. CoRR abs/2102.09475 (2021) - [i9]Anirudh Joshi, Sabri Eyuboglu, Shih-Cheng Huang, Jared Dunnmon, Arjun Soin, Guido A. Davidzon, Akshay Chaudhari, Matthew P. Lungren:
OncoNet: Weakly Supervised Siamese Network to automate cancer treatment response assessment between longitudinal FDG PET/CT examinations. CoRR abs/2108.02016 (2021) - [i8]Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jason Liang, Akshay Chaudhari, Andreas Spanias:
Designing Counterfactual Generators using Deep Model Inversion. CoRR abs/2109.14274 (2021) - [i7]Arjun D. Desai, Batu M. Ozturkler, Christopher M. Sandino, Shreyas Vasanawala, Brian A. Hargreaves, Christopher Ré, John M. Pauly, Akshay S. Chaudhari:
Noise2Recon: A Semi-Supervised Framework for Joint MRI Reconstruction and Denoising. CoRR abs/2110.00075 (2021) - [i6]Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Srini Bala, Daniel J. Beutel, Victor Bittorf, Akshay Chaudhari, Alexander Chowdhury, Cody Coleman, Bala Desinghu, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Junyi Guo, Xinyuan Huang, David Kanter, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Jacob Rosenthal, Abhishek Singh, Jayaraman J. Thiagarajan, Anna Wuest, Maria Xenochristou, Daguang Xu, Poonam Yadav, Michael Rosenthal, Massimo Loda, Jason M. Johnson, Peter Mattson:
MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation. CoRR abs/2110.01406 (2021) - [i5]Joseph Paul Cohen, Joseph D. Viviano, Paul Bertin, Paul Morrison, Parsa Torabian, Matteo Guarrera, Matthew P. Lungren, Akshay Chaudhari, Rupert Brooks, Mohammad Hashir, Hadrien Bertrand:
TorchXRayVision: A library of chest X-ray datasets and models. CoRR abs/2111.00595 (2021) - 2020
- [i4]Arjun D. Desai, Francesco Calivá, Claudia Iriondo, Naji Khosravan, Aliasghar Mortazi, Sachin Jambawalikar, Drew A. Torigian, Jutta Ellermann, Mehmet Akçakaya, Ulas Bagci, Radhika Tibrewala, Io Flament, Matthew O'Brien, Sharmila Majumdar, Mathias Perslev, Akshay Pai, Christian Igel, Erik B. Dam, Sibaji Gaj, Mingrui Yang, Kunio Nakamura, Xiaojuan Li, Cem M. Deniz, Vladimir Juras, Ravinder Regatte, Garry Gold, Brian A. Hargreaves, Valentina Pedoia, Akshay S. Chaudhari:
The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset. CoRR abs/2004.14003 (2020) - [i3]Kevin A. Thomas, Dominik Krzeminski, Lukasz Kidzinski, Rohan Paul, Elka B. Rubin, Eni Halilaj, Marianne S. Black, Akshay Chaudhari, Garry Gold, Scott L. Delp:
Open source software for automatic subregional assessment of knee cartilage degradation using quantitative T2 relaxometry and deep learning. CoRR abs/2012.12406 (2020)
2010 – 2019
- 2019
- [i2]Arjun D. Desai, Garry Gold, Brian A. Hargreaves, Akshay Chaudhari:
Technical Considerations for Semantic Segmentation in MRI using Convolutional Neural Networks. CoRR abs/1902.01977 (2019) - 2018
- [c1]Akshay Chaudhari, Zhongnan Fang, Jin Hyung Lee, Garry Gold, Brian A. Hargreaves:
Deep Learning Super-Resolution Enables Rapid Simultaneous Morphological and Quantitative Magnetic Resonance Imaging. MLMIR@MICCAI 2018: 3-11 - [i1]Akshay Chaudhari, Zhongnan Fang, Jin Hyung Lee, Garry Gold, Brian A. Hargreaves:
Deep Learning Super-Resolution Enables Rapid Simultaneous Morphological and Quantitative Magnetic Resonance Imaging. CoRR abs/1808.04447 (2018)
Coauthor Index
aka: Curtis P. Langlotz
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last updated on 2024-04-25 01:41 CEST by the dblp team
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