arXiv Machine Learning

Insulin4RL: Real-Time Insulin Management in the Intensive Care Unit for Offline Reinforcement Learning

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.

arXiv Machine Learning

Jun 2

MedGym:A Unified Continuous-Time Benchmark for Dynamic Medical Treatment Reinforcement Learning

arXiv:2606. 01028v1 Announce Type: new Abstract: Medical treatment recommendation poses several challenges to reinforcement learning (RL): patient physiology evolves in continuous time, measurements and interventions are performed at irregular intervals, and treatment effects vary substantially across individuals.

By Yuepeng Wang, Ken Kawano, Yongqi Zhou, Yoshihiko Fujisawa, Richard Weiss, Akifumi Wachi, Katsuki Fujisawa, Ying Chen, Mehrshad Sadria, Xin Liu, Kyoung-Sook Kim, Xiao Hu, Sebastien Gros, Xun Shen

reinforcement-learning benchmarks safety

arXiv Machine Learning

Jun 24

Precision Physical Activity Prescription via Reinforcement Learning for Functional Actions

arXiv:2605. 19208v2 Announce Type: replace-cross Abstract: Physical activity (PA) plays an important role in maintaining and improving health.

By Gefei Lin, Rui Miao, Jennifer Sacheck, Xiaoke Zhang

reinforcement-learning

arXiv AI

Jul 13

EHR-MPC: Inference-Time Control for Sepsis Treatment with Generative Patient Digital Twins

arXiv:2607. 08793v1 Announce Type: cross Abstract: Sepsis is a leading cause of mortality, yet optimal treatment policies remain contested.

By Joshua Pickard, Wei Qi, Na Li, Ann Woolley, Lisa Cosimi, Roy Kishony, Deborah Hung

reinforcement-learning

arXiv AI

Aug 5

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents

arXiv:2608. 03606v1 Announce Type: new Abstract: Clinical development is sequential decision-making under uncertainty, where a sponsor must plan a portfolio of experiments from heterogeneous evidence.

By William Bolton, Philip Torr

llms agents reinforcement-learning fine-tuning

arXiv Machine Learning

Jun 30

Interventional Flow Matching: Prospective Dose-Response Forecasting with Velocity-Field Jacobian Regularization

arXiv:2606. 29386v1 Announce Type: new Abstract: Predicting a patient's physiological trajectory under a planned treatment sequence is a prospective interventional problem, not standard time-series extrapolation.

By Amirreza Dolatpour Fathkouhi, Justin Lee, Heman Shakeri

rag diffusion

arXiv AI

2d ago

Removing Temporal Note Redundancy Improves Multimodal Reinforcement Learning for Medicine

arXiv:2608. 14157v1 Announce Type: new Abstract: Mechanical ventilation is a critical life-support intervention, requiring dynamic adjustments to ventilator settings as a patient's condition evolves.

By Chenran Weng, Joo Seung Lee, Malini Mahendra, Anil Aswani

rag reinforcement-learning multimodal

arXiv AI

Jul 13

LongMedBench: Benchmarking Medical Agents for Long-Horizon Clinical Decision-Making

arXiv:2607. 09322v1 Announce Type: new Abstract: In this work, we introduce LongMedBench, a real-world EHR-based benchmark for long-horizon clinical decision-making.

By Yanzhen Chen, Zihan Xu, Xiaocheng Zhang, Zhiting Fan, Weiqi Zhai, Hongxia Xu, Zuozhu Liu

llms rag agents benchmarks

arXiv Machine Learning

Jun 2

Interaction-Limited Safe Continuous-Time RL for Dynamical Medical Treatment

arXiv:2606. 01051v1 Announce Type: new Abstract: Dynamic medical treatment requires deciding treatment intensity and intervention timing, while patient states evolve continuously and adverse events may occur between clinical interactions.

By Xun Shen, Yuepeng Wang, Akifumi Wachi, Yongqi Zhou, Richard Weiss, Yoshihiko Fujisawa, Ken Kawano, Mehrshad Sadria, Ying Chen, Xin Liu, Sebastien Gros, Xiao Hu, Kyoung-Sook Kim, Mengmou Li, Katsuki Fujisawa, Kenji Wakabayashi

reinforcement-learning safety

arXiv AI

Jul 17

Interpretable Language Model for Closed-Loop Type 1 Diabetes Control

arXiv:2607. 14126v1 Announce Type: new Abstract: Type 1 Diabetes (T1D) is a chronic, life-threatening autoimmune condition characterized by the complete destruction of insulin-producing pancreatic beta cells.

By Maya Sarkar

llms reinforcement-learning fine-tuning safety

arXiv Machine Learning

Aug 11

Learning Multi-Timescale Interventions under Safety and Resource Constraints

arXiv:2508. 03875v2 Announce Type: replace Abstract: Many sequential decision problems offer qualitatively different ways of influencing the environment: some interventions act immediately, whereas others induce persistent effects that continue to shape future states long after the decision that initiated them.

By David Mguni, Wanrong Yang, Jing Dong, Ziquan Liu, Muhammad Salman Haleem, Baoxiang Wang, Dominik Wojtczak

agents reinforcement-learning robotics benchmarks safety

arXiv Machine Learning

Jul 21

Enhancing Personalized Bladder Cancer Treatment Through Reinforcement Learning: A Recurrent Patient State Transition Decision Support Framework

arXiv:2607. 16916v1 Announce Type: new Abstract: Bladder cancer treatment requires personalized and adaptive decision-making, particularly for recurrent disease, where treatment effectiveness changes across successive clinical episodes.

By Divyansh Chawla, Anshu Garg, Isshaan Singh

agents reinforcement-learning

arXiv AI

Jun 17

Treatment Response Optimized Clinical Decision Support AI System via Digital Twin Simulation

arXiv:2606. 17405v1 Announce Type: new Abstract: Clinical decision support AI systems (CDSASs) must adapt to evolving patient conditions in real-time while adhering to strict safety constraints.

By Xinyu Qin, Anil K. Sood, Ruiheng Yu, Sara Corvigno, Elaine Stur, Lu Wang

reinforcement-learning safety

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