2 papers
cs.AI2026
Learning Preference-Based Objectives from Clinical Narratives for Dynamic Sepsis Treatment
Daniel J. Tan, Jayne Hui Zhen Chan, Kai Wen Hwang +3
Designing reward functions for reinforcement learning (RL) in healthcare remains challenging because clinically meaningful outcomes are sparse, delayed, and difficult to explicitly…
cs.LG2025
DeepEN: A Deep Reinforcement Learning Framework for Personalized Enteral Nutrition in Critical Care
Daniel Jason Tan, Jiayang Chen, Dilruk Perera +2
Objective: Enteral nutrition (EN) delivery in the ICU remains suboptimal due to limited personalization and uncertainty regarding appropriate calorie, protein, and fluid targets un…