5 citations · 11 across the 5 of their papers we have counts for
5 papers
Identifying Reasons for Contraceptive Switching from Real-World Data Using Large Language Models
Brenda Y. Miao, Christopher YK Williams, Ebenezer Chinedu-Eneh +4
Prescription contraceptives play a critical role in supporting women's reproductive health. With nearly 50 million women in the United States using contraceptives, understanding th…
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 +5
Although supervised machine learning is popular for information extraction from clinical notes, creating large annotated datasets requires extensive domain expertise and is time-co…
Perceptual and technical barriers in sharing and formatting metadata accompanying omics studies
Yu-Ning Huang, Michael I. Love, Cynthia Flaire Ronkowski +13
Metadata, often termed "data about data," is crucial for organizing, understanding, and managing vast omics datasets. It aids in efficient data discovery, integration, and interpre…
Large Language Models as Agents in the Clinic
Nikita Mehandru, Brenda Y. Miao, Eduardo Rodriguez Almaraz +3
Recent developments in large language models (LLMs) have unlocked new opportunities for healthcare, from information synthesis to clinical decision support. These new LLMs are not…
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 +2
Objective: Text mining of clinical notes embedded in electronic medical records is increasingly used to extract patient characteristics otherwise not or only partly available, to a…