Madhumita Sushil

According to our database, Madhumita Sushil authored at least 18 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Updating the Minimum Information about CLinical Artificial Intelligence (MI-CLAIM) checklist for generative modeling research.

Brenda Y. Miao, Irene Y. Chen, Christopher YK Williams, Jaysón M. Davidson, Augusto Garcia-Agundez, Harry Sun, Travis Zack, Atul J. Butte, Madhumita Sushil

CoRR, 2024

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

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., June, 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

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

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

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

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

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

Training a Transferrable Clinical Language Model from 75 million Notes.

Madhumita Sushil, Dana Ludwig, Atul J. Butte, Vivek A. Rudrapatna

Proceedings of the AMIA 2022, 2022

2021

Contextual explanation rules for neural clinical classifiers.

Madhumita Sushil, Simon Suster, Walter Daelemans

Proceedings of the 20th Workshop on Biomedical Language Processing, 2021

Are we there yet? Exploring clinical domain knowledge of BERT models.

Madhumita Sushil, Simon Suster, Walter Daelemans

Proceedings of the 20th Workshop on Biomedical Language Processing, 2021

2020

Distilling neural networks into skipgram-level decision lists.

Madhumita Sushil, Simon Suster, Walter Daelemans

CoRR, 2020

2019

Why can't memory networks read effectively?

Simon Suster, Madhumita Sushil, Walter Daelemans

CoRR, 2019

2018

Patient representation learning and interpretable evaluation using clinical notes.

Madhumita Sushil, Simon Suster, Kim Luyckx, Walter Daelemans

J. Biomed. Informatics, 2018

Rule induction for global explanation of trained models.

Madhumita Sushil, Simon Suster, Walter Daelemans

Proceedings of the Workshop: Analyzing and Interpreting Neural Networks for NLP, 2018

Revisiting neural relation classification in clinical notes with external information.

Simon Suster, Madhumita Sushil, Walter Daelemans

Proceedings of the Ninth International Workshop on Health Text Mining and Information Analysis, 2018

2017

Unsupervised patient representations from clinical notes with interpretable classification decisions.

Madhumita Sushil, Simon Suster, Kim Luyckx, Walter Daelemans

CoRR, 2017