Deep Learning Super-Resolution Enables Rapid Simultaneous Morphological and Quantitative Magnetic Resonance Imaging. - Akshay Chaudhari; Zhongnan Fang; Jin Hyung Lee; Garry Gold; Brian A. Hargreaves (MLMIR@MICCAI, 2018)

Technical Considerations for Semantic Segmentation in MRI using Convolutional Neural Networks. - Arjun D. Desai; Garry Gold; Brian A. Hargreaves; Akshay Chaudhari (CoRR, 2019)

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset. - 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; et al. (CoRR, 2020)

Open source software for automatic subregional assessment of knee cartilage degradation using quantitative T2 relaxometry and deep learning. - Kevin A. Thomas; Dominik Krzeminski; Lukasz Kidzinski; Rohan Paul; Elka B. Rubin; Eni Halilaj; Marianne S. Black; Akshay Chaudhari; Garry Gold; Scott L. Delp (CoRR, 2020)

Development of the Next Generation Hand-Held Doppler with Waveform Phasicity Predictive Capabilities Using Deep Learning. - Adrit Rao; Akshay Chaudhari; Oliver O. Aalami (CLIP/DCL/LL-COVID19/PPML@MICCAI, 2021)

Measuring Robustness in Deep Learning Based Compressive Sensing. - Mohammad Zalbagi Darestani; Akshay S. Chaudhari; Reinhard Heckel (ICML, 2021)

Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays. - Joseph Paul Cohen; Rupert Brooks; Sovann En; Evan Zucker; Anuj Pareek; Matthew P. Lungren; Akshay Chaudhari (MIDL, 2021)

SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation. - 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 (NeurIPS Datasets and Benchmarks, 2021)

Designing Counterfactual Generators using Deep Model Inversion. - Jayaraman J. Thiagarajan; Vivek Sivaraman Narayanaswamy; Deepta Rajan; Jason Liang; Akshay Chaudhari; Andreas Spanias (NeurIPS, 2021)

MRSaiFE: An AI-Based Approach Towards the Real-Time Prediction of Specific Absorption Rate. - Sayim Gokyar; Fraser J. L. Robb; Wolfgang Kainz; Akshay Chaudhari; Simone Angela Winkler (IEEE Access, 2021)

Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Progressive Exaggeration on Chest X-rays. - Joseph Paul Cohen; Rupert Brooks; Sovann En; Evan Zucker; Anuj Pareek; Matthew P. Lungren; Akshay Chaudhari (CoRR, 2021)

OncoNet: Weakly Supervised Siamese Network to automate cancer treatment response assessment between longitudinal FDG PET/CT examinations. - Anirudh Joshi; Sabri Eyuboglu; Shih-Cheng Huang; Jared Dunnmon; Arjun Soin; Guido A. Davidzon; Akshay Chaudhari; Matthew P. Lungren (CoRR, 2021)

Noise2Recon: A Semi-Supervised Framework for Joint MRI Reconstruction and Denoising. - Arjun D. Desai; Batu M. Ozturkler; Christopher M. Sandino; Shreyas Vasanawala; Brian A. Hargreaves; Christopher Ré; John M. Pauly; Akshay S. Chaudhari (CoRR, 2021)

MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation. - 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; et al. (CoRR, 2021)

Author Correction: Low-count whole-body PET with deep learning in a multicenter and externally validated study. - Akshay S. Chaudhari; Erik Mittra; Guido A. Davidzon; Praveen Gulaka; Harsh Gandhi; Adam Brown; Tao Zhang; Shyam Srinivas; Enhao Gong; Greg Zaharchuk; Hossein Jadvar (npj Digit. Medicine, 2021)

Low-count whole-body PET with deep learning in a multicenter and externally validated study. - Akshay S. Chaudhari; Erik Mittra; Guido A. Davidzon; Praveen Gulaka; Harsh Gandhi; Adam Brown; Tao Zhang; Shyam Srinivas; Enhao Gong; Greg Zaharchuk; Hossein Jadvar (npj Digit. Medicine, 2021)

ViLMedic: a framework for research at the intersection of vision and language in medical AI. - Jean-Benoit Delbrouck; Khaled Saab 002; Maya Varma; Sabri Eyuboglu; Pierre J. Chambon; Jared Dunnmon; Juan Zambrano; Akshay Chaudhari; Curtis P. Langlotz (ACL (demo), 2022)

Opportunistic Incidence Prediction of Multiple Chronic Diseases from Abdominal CT Imaging Using Multi-task Learning. - 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 (MICCAI (8), 2022)

Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction. - Beliz Gunel; Arda Sahiner; Arjun D. Desai; Akshay S. Chaudhari; Shreyas Vasanawala; Mert Pilanci; John M. Pauly (MICCAI (6), 2022)

TorchXRayVision: A library of chest X-ray datasets and models. - 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 (MIDL, 2022)

VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI Reconstruction. - Arjun D. Desai; Beliz Gunel; Batu M. Ozturkler; Harris Beg; Shreyas Vasanawala; Brian A. Hargreaves; Christopher Ré; John M. Pauly; Akshay S. Chaudhari (MIDL, 2022)

Correction to "MRSaiFE: An AI-Based Approach Toward the Real-Time Prediction of Specific Absorption Rate". - Sayim Gokyar; Fraser J. L. Robb; Wolfgang Kainz; Akshay Chaudhari; Simone Angela Winkler (IEEE Access, 2022)

Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains. - Pierre J. Chambon; Christian Bluethgen; Curtis P. Langlotz; Akshay Chaudhari (CoRR, 2022)

Data-Limited Tissue Segmentation using Inpainting-Based Self-Supervised Learning. - 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 (CoRR, 2022)

Scale-Agnostic Super-Resolution in MRI using Feature-Based Coordinate Networks. - 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 (CoRR, 2022)

RoentGen: Vision-Language Foundation Model for Chest X-ray Generation. - 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 (CoRR, 2022)

Interactive Span Recommendation for Biomedical Text. - Louis Blankemeier; Theodore Zhao; Robert Tinn; Sid Kiblawi; Yu Gu 017; Akshay Chaudhari; Hoifung Poon; Sheng Zhang 012; Mu Wei; Joseph Preston (ClinicalNLP@ACL, 2023)

Efficient Diagnosis Assignment Using Unstructured Clinical Notes. - Louis Blankemeier; Jason A. Fries; Robert Tinn; Joseph Preston; Nigam Shah; Akshay Chaudhari (ACL (2), 2023)

RadAdapt: Radiology Report Summarization via Lightweight Domain Adaptation of Large Language Models. - 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 (BioNLP@ACL, 2023)

ViLLA: Fine-Grained Vision-Language Representation Learning from Real-World Data. - Maya Varma; Jean-Benoit Delbrouck; Sarah M. Hooper; Akshay Chaudhari; Curtis P. Langlotz (ICCV, 2023)

DDM2: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models. - Tiange Xiang; Mahmut Yurt; Ali B. Syed; Kawin Setsompop; Akshay Chaudhari (ICLR, 2023)

Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays. - Rogier van der Sluijs; Nandita Bhaskhar; Daniel L. Rubin; Curtis P. Langlotz; Akshay S. Chaudhari (MIDL, 2023)

RaLEs: a Benchmark for Radiology Language Evaluations. - Juanma Zambrano Chaves; Nandita Bhaskhar; Maayane Attias; Jean-Benoit Delbrouck; Daniel L. Rubin; Andreas M. Loening; Curtis P. Langlotz; Akshay Chaudhari (NeurIPS, 2023)

Radiology Decision Support System for Selecting Appropriate CT Imaging Titles Using Machine Learning Techniques Based on Electronic Medical Records. - Peyman Shokrollahi; Juan Manuel Zambrano Chaves; Jonathan P. H. Lam; Avishkar Sharma; Debashish Pal; Naeim Bahrami; Akshay S. Chaudhari; Andreas M. Loening (IEEE Access, 2023)

Comp2Comp: Open-Source Body Composition Assessment on Computed Tomography. - Louis Blankemeier; Arjun D. Desai; Juan Manuel Zambrano Chaves; Andrew Wentland; Sally Yao; Eduardo Pontes Reis; Malte E. K. Jensen; Bhanushree Bahl; Khushboo Arora; Bhavik N. Patel; Leon Lenchik; Marc H. Willis; et al. (CoRR, 2023)

The Effect of Counterfactuals on Reading Chest X-rays. - Joseph Paul Cohen; Rupert Brooks; Sovann En; Evan Zucker; Anuj Pareek; Matthew P. Lungren; Akshay Chaudhari (CoRR, 2023)

Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts. - 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; et al. (CoRR, 2023)

A scoping review of portable sensing for out-of-lab anterior cruciate ligament injury prevention and rehabilitation. - Tian Tan 008; 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 (npj Digit. Medicine, 2023)

Self-supervised learning for medical image classification: a systematic review and implementation guidelines. - Shih-Cheng Huang; Anuj Pareek; Malte E. K. Jensen; Matthew P. Lungren; Serena Yeung; Akshay S. Chaudhari (npj Digit. Medicine, 2023)

Convolutional neural networks for prediction of geometrical errors in incremental sheet metal forming. - Darren Wei Wen Low; Akshay Chaudhari; Dharmesh Kumar; A. Senthil Kumar (J. Intell. Manuf., 2023)

Federated benchmarking of medical artificial intelligence with MedPerf. - 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; et al. (Nat. Mac. Intell., 2023)

OpenCap: Human movement dynamics from smartphone videos. - Scott D. Uhlrich; Antoine Falisse; Lukasz Kidzinski; Julie Muccini; Michael Ko; Akshay S. Chaudhari; Jennifer L. Hicks; Scott L. Delp (PLoS Comput. Biol., 2023)

MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records. - 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 002; Birju S. Patel; Chia-Chun Chiang; et al. (AAAI, 2024)

GREEN: Generative Radiology Report Evaluation and Error Notation. - Sophie Ostmeier; Justin Xu; Zhihong Chen; Maya Varma; Louis Blankemeier; Christian Bluethgen; Arne Edward Michalson; Michael E. Moseley; Curtis P. Langlotz; Akshay Chaudhari; Jean-Benoit Delbrouck (EMNLP (Findings), 2024)

SOE: SO(3)-Equivariant 3D MRI Encoding. - Shizhe He; Magdalini Paschali; Jiahong Ouyang; Adnan Masood; Akshay Chaudhari; Ehsan Adeli-Mosabbeb (MLCN@MICCAI, 2024)

Spectral Graph Sample Weighting for Interpretable Sub-cohort Analysis in Predictive Models for Neuroimaging. - Magdalini Paschali; Yu Hang Jiang; Spencer Siegel; Camila González; Kilian M. Pohl; Akshay Chaudhari; Qingyu Zhao (PRIME@MICCAI, 2024)

RaVL: Discovering and Mitigating Spurious Correlations in Fine-Tuned Vision-Language Models. - Maya Varma; Jean-Benoit Delbrouck; Zhihong Chen; Akshay Chaudhari; Curtis P. Langlotz (NeurIPS, 2024)

CheXagent: Towards a Foundation Model for Chest X-Ray Interpretation. - 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; et al. (CoRR, 2024)

A Benchmark of Domain-Adapted Large Language Models for Generating Brief Hospital Course Summaries. - 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 (CoRR, 2024)

Deep Learning for Accelerated and Robust MRI Reconstruction: a Review. - Reinhard Heckel; Mathews Jacob; Akshay Chaudhari; Or Perlman; Efrat Shimron (CoRR, 2024)

Almanac Copilot: Towards Autonomous Electronic Health Record Navigation. - Cyril Zakka; Joseph Cho; Gracia Fahed; Rohan Shad; Michael Moor; Robyn Fong; Dhamanpreet Kaur; Vishnu Ravi; Oliver O. Aalami; Roxana Daneshjou; Akshay Chaudhari; William Hiesinger (CoRR, 2024)

MediSyn: Text-Guided Diffusion Models for Broad Medical 2D and 3D Image Synthesis. - Joseph Cho; Cyril Zakka; Rohan Shad; Ross Wightman; Akshay Chaudhari; William Hiesinger (CoRR, 2024)

Merlin: A Vision Language Foundation Model for 3D Computed Tomography. - 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; et al. (CoRR, 2024)

OpenCapBench: A Benchmark to Bridge Pose Estimation and Biomechanics. - Yoni Gozlan; Antoine Falisse; Scott D. Uhlrich; Anthony A. Gatti; Michael Black; Akshay Chaudhari (CoRR, 2024)

LieRE: Generalizing Rotary Position Encodings. - Sophie Ostmeier; Brian Axelrod; Michael E. Moseley; Akshay Chaudhari; Curtis P. Langlotz (CoRR, 2024)

Enhance the Image: Super Resolution using Artificial Intelligence in MRI. - Ziyu Li; Zihan Li; Haoxiang Li; Qiuyun Fan; Karla L. Miller; Wenchuan Wu 003; Akshay S. Chaudhari; Qiyuan Tian (CoRR, 2024)

Detecting Underdiagnosed Medical Conditions with Deep Learning-Based Opportunistic CT Imaging. - Asad Aali; Andrew Johnston; Louis Blankemeier; Dave Van Veen; Laura T. Derry; David Svec; Jason Hom; Robert D. Boutin; Akshay S. Chaudhari (CoRR, 2024)

Preference Fine-Tuning for Factuality in Chest X-Ray Interpretation Models Without Human Feedback. - Dennis Hein; Zhihong Chen; Sophie Ostmeier; Justin Xu; Maya Varma; Eduardo Pontes Reis; Arne Edward Michalson; Christian Bluethgen; Hyun Joo Shin; Curtis P. Langlotz; Akshay S. Chaudhari (CoRR, 2024)

Evaluating and Improving the Effectiveness of Synthetic Chest X-Rays for Medical Image Analysis. - Eva Prakash; Jeya Maria Jose Valanarasu; Zhihong Chen; Eduardo Pontes Reis; Andrew Johnston; Anuj Pareek; Christian Bluethgen; Sergios Gatidis; Cameron Olsen; Akshay Chaudhari; Andrew Y. Ng; Curtis P. Langlotz (CoRR, 2024)

Foundation Models in Radiology: What, How, When, Why and Why Not. - Magdalini Paschali; Zhihong Chen; Louis Blankemeier; Maya Varma; Alaa Youssef; Christian Bluethgen; Curtis P. Langlotz; Sergios Gatidis; Akshay Chaudhari (CoRR, 2024)

Best Practices for Large Language Models in Radiology. - Christian Bluethgen; Dave Van Veen; Cyril Zakka; Katherine Link; Aaron Fanous; Roxana Daneshjou; Thomas Frauenfelder; Curtis P. Langlotz; Sergios Gatidis; Akshay Chaudhari (CoRR, 2024)

Regulating radiology AI medical devices that evolve in their lifecycle. - Camila González; Moritz Fuchs; Daniel Pinto dos Santos; Philipp Matthies; Manuel Trenz; Maximilian Grüning; Akshay Chaudhari; David B. Larson; Ahmed E. Othman; Moon Kim 002; Felix Nensa; Anirban Mukhopadhyay 003 (CoRR, 2024)

Self-Supervised Learning Improves Accuracy and Data Efficiency for IMU-Based Ground Reaction Force Estimation. - Tian Tan 008; Peter B. Shull; Jennifer L. Hicks; Scott D. Uhlrich; Akshay S. Chaudhari (IEEE Trans. Biomed. Eng., 2024)

CheXalign: Preference fine-tuning in chest X-ray interpretation models without human feedback. - Dennis Hein; Zhihong Chen; Sophie Ostmeier; Justin Xu; Maya Varma; Eduardo Pontes Reis; Arne Edward Michalson; Christian Bluethgen; Hyun Joo Shin; Curtis P. Langlotz; Akshay S. Chaudhari (ACL (1), 2025)

Eyes Tell the Truth: GazeVal Highlights Shortcomings of Generative AI in Medical Imaging. - David C. Wong 005; Bin Wang 068; Gorkem Durak; Marouane Tliba; Akshay Chaudhari; Aladine Chetouani; Ahmet Enis Çetin; Cagdas Topel; Nicolo Gennaro; Camila Lopes Vendrami; Tugce Agirlar Trabzonlu; Amir Ali Rahsepar; et al. (CVPR Workshops, 2025)

Time-to-Event Pretraining for 3D Medical Imaging. - Zepeng Frazier Huo; Jason Alan Fries; Alejandro Lozano; Jeya Maria Jose Valanarasu; Ethan Steinberg; Louis Blankemeier; Akshay S. Chaudhari; Curtis P. Langlotz; Nigam Shah (ICLR, 2025)

OpenCapBench: A Benchmark to Bridge Pose Estimation and Biomechanics. - Yoni Gozlan; Antoine Falisse; Scott D. Uhlrich; Anthony A. Gatti; Michael Black; Jennifer L. Hicks; Scott L. Delp; Akshay Chaudhari (WACV, 2025)

A dataset and benchmark for hospital course summarization with adapted large language models. - 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 (J. Am. Medical Informatics Assoc., 2025)

Identifying Spurious Correlations using Counterfactual Alignment. - Joseph Paul Cohen; Louis Blankemeier; Akshay S. Chaudhari (Trans. Mach. Learn. Res., 2025)

Embedding-Driven Diversity Sampling to Improve Few-Shot Synthetic Data Generation. - Iván López; Fateme Nateghi Haredasht; Kaitlin Caoili; Jonathan H. Chen; Akshay Chaudhari (CoRR, 2025)

Explaining 3D Computed Tomography Classifiers with Counterfactuals. - Joseph Paul Cohen; Louis Blankemeier; Akshay Chaudhari (CoRR, 2025)

MedVAE: Efficient Automated Interpretation of Medical Images with Large-Scale Generalizable Autoencoders. - Maya Varma; Ashwin Kumar; Rogier van der Sluijs; Sophie Ostmeier; Louis Blankemeier; Pierre J. Chambon; Christian Bluethgen; Jip Prince; Curtis P. Langlotz; Akshay Chaudhari (CoRR, 2025)

ShapeMed-Knee: A Dataset and Neural Shape Model Benchmark for Modeling 3D Femurs. - Anthony A. Gatti; Louis Blankemeier; Dave Van Veen; Brian A. Hargreaves; Scott L. Delp; Garry E. Gold; Feliks Kogan; Akshay S. Chaudhari (IEEE Trans. Medical Imaging, 2025)

Efficient Noise Calculation in Deep Learning-based MRI Reconstructions. - Onat Dalmaz; Arjun D. Desai; Reinhard Heckel; Tolga Çukur; Akshay S. Chaudhari; Brian A. Hargreaves (CoRR, 2025)

Aligning Large Language Models with Healthcare Stakeholders: A Pathway to Trustworthy AI Integration. - Kexin Ding; Mu Zhou; Akshay Chaudhari; Shaoting Zhang 001; Dimitris N. Metaxas (CoRR, 2025)

Automated Real-time Assessment of Intracranial Hemorrhage Detection AI Using an Ensembled Monitoring Model (EMM). - Zhongnan Fang; Andrew Johnston; Lina Cheuy; Hye Sun Na; Magdalini Paschali; Camila González; Bonnie A. Armstrong; Arogya Koirala; Derrick Laurel; Andrew Campion; Michael Iv; Akshay S. Chaudhari; et al. (CoRR, 2025)

MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks. - Suhana Bedi; Hejie Cui; Miguel Fuentes; Alyssa Unell; Michael Wornow; Juan M. Banda; Nikesh Kotecha; Timothy Keyes; Yifan Mai 001; Mert Oez; Hao Qiu; Shrey Jain; et al. (CoRR, 2025)

Marker Data Enhancement for Markerless Motion Capture. - Antoine Falisse; Scott D. Uhlrich; Akshay S. Chaudhari; Jennifer L. Hicks; Scott L. Delp (IEEE Trans. Biomed. Eng., 2025)

Expert-level validation of AI-generated medical text with scalable language models. - Asad Aali; Vasiliki Bikia; Maya Varma; Nicole Chiou; Sophie Ostmeier; Arnav Singhvi; Magdalini Paschali; Ashwin Kumar; Andrew Johnston; Karimar Amador-Martinez; Eduardo Juan Perez Guerrero; Paola Naovi Cruz Rivera; et al. (CoRR, 2025)