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20202026
most citedGeneralization in Healthcare AI: Evaluation of a Clinical Large Language Model

8 citations · 12 across the 7 of their papers we have counts for

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Showing cs.CLShow all

6 papers · 1 filter

cs.CL20251 cited

Generalist Foundation Models Are Not Clinical Enough for Hospital Operations

Lavender Y. Jiang, Angelica Chen, Xu Han +16

Hospitals and healthcare systems rely on operational decisions that determine patient flow, cost, and quality of care. Despite strong performance on medical knowledge and conversat…

cs.CL2025

BPQA Dataset: Evaluating How Well Language Models Leverage Blood Pressures to Answer Biomedical Questions

Chi Hang, Ruiqi Deng, Lavender Yao Jiang +4

Clinical measurements such as blood pressures and respiration rates are critical in diagnosing and monitoring patient outcomes. It is an important component of biomedical data, whi…

cs.CL2024

Refining Packing and Shuffling Strategies for Enhanced Performance in Generative Language Models

Yanbing Chen, Ruilin Wang, Zihao Yang +2

Packing and shuffling tokens is a common practice in training auto-regressive language models (LMs) to prevent overfitting and improve efficiency. Typically documents are concatena…

cs.CL20248 cited

Generalization in Healthcare AI: Evaluation of a Clinical Large Language Model

Salman Rahman, Lavender Yao Jiang, Saadia Gabriel +3

Advances in large language models (LLMs) provide new opportunities in healthcare for improved patient care, clinical decision-making, and enhancement of physician and administrator…

cs.CL20231 cited

Making the Most Out of the Limited Context Length: Predictive Power Varies with Clinical Note Type and Note Section

Hongyi Zheng, Yixin Zhu, Lavender Yao Jiang +2

Recent advances in large language models have led to renewed interest in natural language processing in healthcare using the free text of clinical notes. One distinguishing charact…

cs.CL20223 cited

Language Model Classifier Aligns Better with Physician Word Sensitivity than XGBoost on Readmission Prediction

Grace Yang, Ming Cao, Lavender Y. Jiang +6

Traditional evaluation metrics for classification in natural language processing such as accuracy and area under the curve fail to differentiate between models with different predi…