arXiv:2503. 19158v3 Announce Type: replace Abstract: Type 1 Diabetes (T1D) management is a complex task due to many variability factors.
By Stefano De Carli, Nicola Licini, Davide Previtali, Fabio Previdi, Antonio Ferramosca
arXiv:2606. 19481v1 Announce Type: new Abstract: Offline reinforcement learning (ORL) offers the potential to improve the quality of clinical decision-making using historical electronic health record (EHR) data.
By Thomas Frost, Steve Harris
arXiv:2606. 24145v1 Announce Type: new Abstract: Large language models (LLMs) can produce clinically fluent recommendations for type 2 diabetes while failing to satisfy guideline constraints or explicitly justify lifestyle-related glycemic claims.
By Saba A. Farahani, Hung Cao, Ramesh Jain, Amir M. Rahmani
arXiv:2606. 12699v1 Announce Type: cross Abstract: Type 2 Diabetes (T2D) poses an increasing global health threat, demanding effective glycemic assessment to support personalized and improved diabetes care.
By Yifan Gao, Yanmin Gong, Yun Shi, Yuanxiong Guo
arXiv:2606. 16149v3 Announce Type: replace Abstract: Rare disease diagnosis depends on expert reasoning that is scarce and difficult to transfer; off-the-shelf large language models (LLMs) rank the correct disease first in only 35.
By Minh-Ha Nguyen, Erica Gray, Bryce A. Schuler, Kevin W. Byram, Chih-Ting Yang, Fan Ma, Hua Xu, Wu-Chen Su, Chao Yan, Wei-Qi Wei, Adam Wright, Lisa Bastarache, Josh Peterson, Lingyao Li, Siyuan Ma, Undiagnosed Diseases Network, Rizwan Hamid, Thomas A. Cassini, Cathy Shyr
arXiv:2604. 23954v2 Announce Type: replace Abstract: Artificial Intelligence (AI) and Machine Learning (ML) models used in clinical settings are increasingly deployed to support clinical decision-making.
By Ioannis Bilionis, Ricardo C. Berrios, Luis Fernandez-Luque, Carlos Castillo