4 citations · 5 across the 3 of their papers we have counts for
4 papers
Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning
Jiacheng Lin, Zhenbang Wu, Jimeng Sun
We present EHRMIND, a practical recipe for adapting large language models (LLMs) to complex clinical reasoning tasks using reinforcement learning with verifiable rewards (RLVR). Wh…
Reinforcement Learning for Out-of-Distribution Reasoning in LLMs: An Empirical Study on Diagnosis-Related Group Coding
Hanyin Wang, Zhenbang Wu, Gururaj Kolar +4
Diagnosis-Related Group (DRG) codes are essential for hospital reimbursement and operations but require labor-intensive assignment. Large Language Models (LLMs) struggle with DRG c…
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
Peng Xia, Ze Chen, Juanxi Tian +21
Artificial intelligence has significantly impacted medical applications, particularly with the advent of Medical Large Vision Language Models (Med-LVLMs), sparking optimism for the…
PIE: Simulating Disease Progression via Progressive Image Editing
Kaizhao Liang, Xu Cao, Kuei-Da Liao +6
Disease progression simulation is a crucial area of research that has significant implications for clinical diagnosis, prognosis, and treatment. One major challenge in this field i…