Chaudhari, Akshay S.

Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts

Veen, D. V., Uden, C. V., Blankemeier, L., Delbrouck, J.-B., Aali, A., Bluethgen, C., Pareek, A., Polacin, M., Reis, E. P., Seehofnerova, A., et al. (2023) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 892

Adapted large language models can outperform medical experts in clinical text summarization

Van Veen, D., Van Uden, C., Blankemeier, L., Delbrouck, J.-B., Aali, A., Bluethgen, C., Pareek, A., Polacin, M., Reis, E. P., Seehofnerová, A., et al. (2024) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 891

Self-supervised learning for medical image classification: a systematic review and implementation guidelines

Huang, S.-C., Pareek, A., Jensen, M., Lungren, M. P., Yeung, S., & Chaudhari, A. S. (2023) · npj Digital Medicine

Domain Adaptation and Few-Shot LearningArtificial Intelligence in Healthcare and Education

Cited by 479

Super‐resolution musculoskeletal MRI using deep learning

Chaudhari, A. S., Fang, Z., Kogan, F., Wood, J., Stevens, K. J., Gibbons, E. K., Lee, J. H., Gold, G. E., & Hargreaves, B. A. (2018) · Magnetic Resonance in Medicine

Advanced Image Processing TechniquesAdvanced MRI Techniques and Applications

Cited by 406

Federated benchmarking of medical artificial intelligence with MedPerf

Karargyris, A., Umeton, R., Sheller, M. J., Aristizabal, A., George, J., Wuest, A., Pati, S., Kassem, H., Zenk, M., Baid, U., et al. (2023) · Nature Machine Intelligence

Artificial Intelligence in Healthcare and EducationPrivacy-Preserving Technologies in Data

Cited by 188

Generating synthetic data for medical imaging

Koetzier, L. R., Wu, J., Mastrodicasa, D., Lutz, A., Chung, M., Koszek, W. A., Pratap, J., Chaudhari, A. S., Rajpurkar, P., Lungren, M. P., et al. (2024) · Radiology

Artificial Intelligence in Healthcare and EducationGenerative Adversarial Networks and Image Synthesis

Cited by 111

A vision–language foundation model for the generation of realistic chest X-ray images

Bluethgen, C., Chambon, P., Delbrouck, J.-B., van der Sluijs, R., Połacin, M., Zambrano Chaves, J. M., Abraham, T. M., Purohit, S., Langlotz, C. P., & Chaudhari, A. S. (2024) · Nature Biomedical Engineering

Generative Adversarial Networks and Image SynthesisArtificial Intelligence in Healthcare and Education

Cited by 108

Low-count whole-body PET with deep learning in a multicenter and externally validated study

Chaudhari, A. S., Mittra, E., Davidzon, G. A., Gulaka, P., Gandhi, H., Brown, A., Zhang, T., Srinivas, S., Gong, E., Zaharchuk, G., et al. (2021) · npj Digital Medicine

Medical Imaging Techniques and ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 83

TorchXRayVision: A library of chest X-ray datasets and models

Cohen, J. P., Viviano, J. D., Bertin, P., Morrison, P., Torabian, P., Guarrera, M., Lungren, M. P., Chaudhari, A., Brooks, R., Hashir, M., et al. (2021) · arXiv

COVID-19 diagnosis using AIRadiomics and Machine Learning in Medical Imaging

Cited by 82

MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records

Fleming, S. L., Lozano, A., Haberkorn, W. J., Jindal, J. A., Reis, E., Thapa, R., Blankemeier, L., Genkins, J. Z., Steinberg, E., Nayak, A., et al. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 66

MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records

Fleming, S. L., Lozano, A., Haberkorn, W. J., Jindal, J. A., Reis, E. P., Thapa, R., Blankemeier, L., Genkins, J. Z., Steinberg, E., Nayak, A., et al. (2023) · arXiv

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 65

GREEN: Generative Radiology Report Evaluation and Error Notation

Ostmeier, S., Xu, J., Chen, Z., Varma, M., Blankemeier, L., Bluethgen, C., Md, A. E. M., Moseley, M., Langlotz, C., Chaudhari, A. S., et al. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024

Artificial Intelligence in Healthcare and EducationBiomedical Text Mining and Ontologies

Cited by 59

Holistic evaluation of large language models for medical tasks with MedHELM

Bedi, S., Cui, H., Fuentes, M., Unell, A., Wornow, M., Banda, J. M., Kotecha, N., Keyes, T., Mai, Y., Oez, M., et al. (2026) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 59

A clinically accessible small multimodal radiology model and evaluation metric for chest X-ray findings

Zambrano Chaves, J. M., Huang, S.-C., Xu, Y., Xu, H., Usuyama, N., Zhang, S., Wang, F., Xie, Y., Khademi, M., Yang, Z., et al. (2025) · Nature Communications

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 45

A dataset and benchmark for hospital course summarization with adapted large language models

Aali, A., Van Veen, D., Arefeen, Y. I., Hom, J., Bluethgen, C., Reis, E. P., Gatidis, S., Clifford, N., Daws, J., Tehrani, A. S., et al. (2025) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 32

RadAdapt: Radiology Report Summarization via Lightweight Domain Adaptation of Large Language Models

Van Veen, D., Van Uden, C., Attias, M., Pareek, A., Bluethgen, C., Polacin, M., Chiu, W., Delbrouck, J.-B., Zambrano Chaves, J., Langlotz, C., et al. (2023) · The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks

Biomedical Text Mining and OntologiesTopic Modeling

Cited by 25

Reporting checklist for foundation and large language models in medical research (REFINE): an international consensus guideline

Mese, I., D’Antonoli, T. A., Bluethgen, C., Bressem, K., Cuocolo, R., Chaudhari, A., Tejani, A. S., Isaac, A., Ponsiglione, A., Meddeb, A., et al. (2026) · Diagnostic and Interventional Radiology

Artificial Intelligence in Healthcare and EducationMeta-analysis and systematic reviews

Cited by 17

Sociodemographic Differences Among Patients Receiving Coronary Artery Calcium Imaging vs Nongated Chest Computed Tomography Imaging

Peng, A. W., Skye, M., Jain, S. S., Dudum, R., Maron, D. J., Din, N., Patel, B. N., Chaudhari, A. S., Sandhu, A. T., & Rodriguez, F. (2024) · JACC: Advances

Cardiac Imaging and DiagnosticsCoronary Interventions and Diagnostics

Cited by 6

Effects of Real-Time Notification of AI-Detected Incidental Coronary Artery Calcium on Statin Prescription: The NOTIFY-PICTURE Trial

Dudum, R., Jain, S. S., Mastrodicasa, D., Furst, A., Xu, S., Ngo, S., Eng, D., Khandwala, N., Sousa, D., Chaudhari, A., et al. (2026) · Circulation

Cardiac Imaging and DiagnosticsLipoproteins and Cardiovascular Health

Cited by 5

Statin Therapy Persistence Following Opportunistic Screening for Coronary Artery Calcium on Nongated Chest CTs

Bouladian, S. G., Ngo, S., Mastrodicasa, D., Eng, D., Khandwala, N., Sousa, D., Chaudhari, A. S., Maron, D. J., Rodriguez, F., & Sandhu, A. T. (2025) · JACC: Cardiovascular Imaging

Cardiac Imaging and DiagnosticsLipoproteins and Cardiovascular Health

Cited by 3

RaLEs: a Benchmark for Radiology Language Evaluations

Chaves, J. Z., Bhaskhar, N., Attias, M., Delbrouck, J.-B., Rubin, D., Loening, A., Langlotz, C., & Chaudhari, A. (2023) · Advances in Neural Information Processing Systems 36

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 0