Unsupervised patient representations from clinical notes with interpretable classification decisions. - Madhumita Sushil; Simon Suster; Kim Luyckx; Walter Daelemans (CoRR, 2017)

Revisiting neural relation classification in clinical notes with external information. - Simon Suster; Madhumita Sushil; Walter Daelemans (Louhi@EMNLP, 2018)

Rule induction for global explanation of trained models. - Madhumita Sushil; Simon Suster; Walter Daelemans (BlackboxNLP@EMNLP, 2018)

Patient representation learning and interpretable evaluation using clinical notes. - Madhumita Sushil; Simon Suster; Kim Luyckx; Walter Daelemans (J. Biomed. Informatics, 2018)

Why can't memory networks read effectively? - Simon Suster; Madhumita Sushil; Walter Daelemans (CoRR, 2019)

Distilling neural networks into skipgram-level decision lists. - Madhumita Sushil; Simon Suster; Walter Daelemans (CoRR, 2020)

Are we there yet? Exploring clinical domain knowledge of BERT models. - Madhumita Sushil; Simon Suster; Walter Daelemans (BioNLP@NAACL-HLT, 2021)

Contextual explanation rules for neural clinical classifiers. - Madhumita Sushil; Simon Suster; Walter Daelemans (BioNLP@NAACL-HLT, 2021)

Training a Transferrable Clinical Language Model from 75 million Notes. - Madhumita Sushil; Dana Ludwig; Atul J. Butte; Vivek A. Rudrapatna (AMIA, 2022)

Developing a general-purpose clinical language inference model from a large corpus of clinical notes. - Madhumita Sushil; Dana Ludwig; Atul J. Butte; Vivek A. Rudrapatna (CoRR, 2022)

Topic Modeling on Clinical Social Work Notes for Exploring Social Determinants of Health Factors. - Shenghuan Sun; Travis Zack; Madhumita Sushil; Atul J. Butte (CoRR, 2022)

Cross-institution text mining to uncover clinical associations: a case study relating social factors and code status in intensive care medicine. - Madhumita Sushil; Atul J. Butte; Ewoud Schuit; Maarten van Smeden; Artuur M. Leeuwenberg (CoRR, 2023)

Revealing the impact of social circumstances on the selection of cancer therapy through natural language processing of social work notes. - Shenghuan Sun; Travis Zack; Christopher Y. K. Williams; Atul J. Butte; Madhumita Sushil (CoRR, 2023)

Extracting detailed oncologic history and treatment plan from medical oncology notes with large language models. - Madhumita Sushil; Vanessa E. Kennedy; Brenda Y. Miao; Divneet Mandair; Travis Zack; Atul J. Butte (CoRR, 2023)

Large Language Models as Agents in the Clinic. - Nikita Mehandru; Brenda Y. Miao; Eduardo Rodriguez Almaraz; Madhumita Sushil; Atul J. Butte; Ahmed M. Alaa (CoRR, 2023)

Bottom-up and top-down paradigms of artificial intelligence research approaches to healthcare data science using growing real-world big data. - Michelle Wang; Madhumita Sushil; Brenda Y. Miao; Atul J. Butte (J. Am. Medical Informatics Assoc., 2023)

A comparative study of zero-shot inference with large language models and supervised modeling in breast cancer pathology classification. - Madhumita Sushil; Travis Zack; Divneet Mandair; Zhiwei Zheng; Ahmed Wali; Yan-Ning Yu; Yuwei Quan; Atul J. Butte (CoRR, 2024)

Updating the Minimum Information about CLinical Artificial Intelligence (MI-CLAIM) checklist for generative modeling research. - Brenda Y. Miao; Irene Y. Chen; Christopher Y. K. Williams; Jaysón M. Davidson; Augusto Garcia-Agundez; Harry Sun; Travis Zack; Atul J. Butte; Madhumita Sushil (CoRR, 2024)

Biomedical Large Languages Models Seem not to be Superior to Generalist Models on Unseen Medical Data. - Felix J. Dorfner; Amin Dada; Felix Busch; Marcus R. Makowski; Tianyu Han; Daniel Truhn; Jens Kleesiek; Madhumita Sushil; Jacqueline Lammert; Lisa C. Adams; Keno K. Bressem (CoRR, 2024)

A comparative study of large language model-based zero-shot inference and task-specific supervised classification of breast cancer pathology reports. - Madhumita Sushil; Travis Zack; Divneet Mandair; Zhiwei Zheng; Ahmed Wali; Yan-Ning Yu; Yuwei Quan; Dmytro Lituiev; Atul J. Butte (J. Am. Medical Informatics Assoc., 2024)

Evaluating large language models as agents in the clinic. - Nikita Mehandru; Brenda Y. Miao; Eduardo Rodriguez Almaraz; Madhumita Sushil; Atul J. Butte; Ahmed M. Alaa (npj Digit. Medicine, 2024)

Evaluating the effectiveness of biomedical fine-tuning for large language models on clinical tasks. - Felix J. Dorfner; Amin Dada; Felix Busch; Marcus R. Makowski; Tianyu Han; Daniel Truhn; Jens Kleesiek; Madhumita Sushil; Lisa C. Adams; Keno K. Bressem (J. Am. Medical Informatics Assoc., 2025)

Robustness tests for biomedical foundation models should tailor to specification. - R. Patrick Xian; Noah R. Baker; Tom David; Qiming Cui; A Jay Holmgren; Stefan Bauer; Madhumita Sushil; Reza Abbasi-Asl (CoRR, 2025)

Barriers in Integrating Medical Visual Question Answering into Radiology Workflows: A Scoping Review and Clinicians' Insights. - Deepali Mishra; Chaklam Silpasuwanchai; Ashutosh Modi; Madhumita Sushil; Sorayouth Chumnanvej (CoRR, 2025)