Publications

Datta S denotes my name in the byline. * equal contribution · † corresponding author. Full author lists are given for first- or senior-authored work; middle-author work is listed with "et al." — see the DOI for the complete author list.

Selected

  • Zhou HY, Acosta JN, Adithan S, Datta S, Topol EJ, Rajpurkar P. MedVersa: a generalist foundation model for diverse medical imaging tasks. NEJM AI. 2026;3(4). — DOI
  • Datta S*, Buchireddygari D*, Kaza LVC, Bhalke M, Singh K, Pandey A, et al. Radiology's Last Exam (RadLE): benchmarking frontier multimodal AI against human experts and a taxonomy of visual reasoning errors in radiology. arXiv:2509.25559. Submitted 29 Sep 2025. Preprint (* co-first authors). — arXiv
  • Pate S, Farooq A, Datta S, Sheikh MA, Kumar A, Mishra D. Fine-grained rib fracture diagnosis with hyperbolic embeddings: a detailed annotation framework and multi-label classification model. In: MICCAI 2025. LNCS 15974. Springer; 2025:218–227. — DOI
  • Datta S, Sarangi PK. From chatbots to agentic workflows: ensuring responsible deployment of large language models in radiology. Indian Journal of Radiology & Imaging. 2026;36(2):286–288. Epub 21 Aug 2025. — DOI
  • Sarangi PK, Datta S, Panda BB, Panda S, Mondal H. Evaluating ChatGPT-4's performance in identifying radiological anatomy in FRCR Part 1 examination questions. Indian Journal of Radiology & Imaging. 2025;35(2):287–294. Epub 4 Nov 2024. — DOI
  • Datta S. Artificial intelligence in interventional radiology. In: Artificial Intelligence in Medicine. Springer; 2021:1–12. — DOI

Full list

Journal articles

  • Zhou HY, Acosta JN, Adithan S, Datta S, Topol EJ, Rajpurkar P. MedVersa: a generalist foundation model for diverse medical imaging tasks. NEJM AI. 2026;3(4). — DOI
  • Datta S, Sarangi PK. From chatbots to agentic workflows: ensuring responsible deployment of large language models in radiology. Indian Journal of Radiology & Imaging. 2026;36(2):286–288. Epub 21 Aug 2025. — DOI
  • Sarangi PK, Mondal H, Datta S. Reply to comments on "Evaluating ChatGPT-4's performance in identifying radiological anatomy in FRCR Part 1 examination questions." Indian Journal of Radiology & Imaging. 2026. Online 16 Feb 2026. — DOI
  • Sarangi PK, Datta S, Panda BB, Panda S, Mondal H. Evaluating ChatGPT-4's performance in identifying radiological anatomy in FRCR Part 1 examination questions. Indian Journal of Radiology & Imaging. 2025;35(2):287–294. Epub 4 Nov 2024. — DOI
  • Sarangi PK, Datta S, Swarup MS, Panda S, Nayak DSK, Malik A, Datta A, Mondal H. Radiologic decision-making for imaging in pulmonary embolism: accuracy and reliability of large language models. Indian Journal of Radiology & Imaging. 2024;34(4):653–660. — DOI
  • Sarangi PK, Datta S, Mondal H. Comment on: ChatGPT: chasing the storm in radiology training and education. Indian Journal of Radiology & Imaging. 2024;34(4):792–794. — DOI
  • Ellappan K, Datta S, Muthuraj M, et al. Evaluation of factors influencing M. tuberculosis complex recovery and contamination rates in MGIT960. Indian Journal of Tuberculosis. 2020;67(4):466–471. — DOI

Refereed proceedings

  • Pate S, Farooq A, Datta S, Sheikh MA, Kumar A, Mishra D. Fine-grained rib fracture diagnosis with hyperbolic embeddings: a detailed annotation framework and multi-label classification model. In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2025. LNCS 15974. Springer; 2025:218–227. — DOI · arXiv
  • Dabass M, Chandalia A, Datta S, Mahapatra D. Attention learning-enabled 3D cGAN for lung nodule segmentation. IJCACI 2022 (Algorithms for Intelligent Systems). Springer, 2024:313–326. — DOI
  • Dabass M, Chandalia A, Datta S, Mahapatra D. ALE-GAN: 3D conditional GAN with attention learning modules. ADCIS 2023 (LNNS 890). Springer, 2024:353–363. — DOI
  • Dabass M, Chandalia A, Senasi R, Datta S. Attention and residual-atrous convolutional learning-based CNN architecture for lung nodule segmentation and classification. ADCIS 2023 (LNNS 893). Springer, 2024:171–181. — DOI

Book chapters

  • Datta S. Artificial intelligence in interventional radiology. In: Artificial Intelligence in Medicine. Springer; 2021:1–12. — DOI

Preprints & technical reports

  • Datta S*, Buchireddygari D*, Kaza LVC, Bhalke M, Singh K, Pandey A, et al. Radiology's Last Exam (RadLE): benchmarking frontier multimodal AI against human experts and a taxonomy of visual reasoning errors in radiology. arXiv:2509.25559. Submitted 29 Sep 2025. Preprint (* co-first authors). — arXiv
  • Datta S, Buchireddygari D, Bhatti HBS, and the CRASH Lab team. Radiology's Last Exam 2.0: are we ready for autonomous AI in radiology? CRASH Lab technical report and leaderboard. Released Jul 2026. Full peer-reviewed manuscript in development. — Technical report