arXiv Machine Learning

Proactive Inpatient Bed Requests for Emergency Department Admissions

arXiv:2607. 15432v1 Announce Type: cross Abstract: Emergency department (ED) boarding occurs when admitted patients remain in the ED while awaiting inpatient beds.

arXiv Machine Learning

Aug 6

Differentiating Through Dual Prices: End-to-End Policy Learning Under Capacity Constraints

arXiv:2608. 04669v1 Announce Type: new Abstract: Many social services assign scarce resources, such as housing assistance or hospital interventions, to people who arrive one at a time: each arrival must receive a decision immediately, and the long-run usage of every resource must stay within its capacity.

By Mohammadsaeed Haghi, Mahdi Salmani, Nima Kelidari

arXiv AI

Jul 1

Qualified Educational Capacity Planning under Heterogeneous Student Support Needs: A Synthetic Benchmark and Decision-Support Framework

arXiv:2606. 30650v1 Announce Type: cross Abstract: Educational support services often face a qualified-capacity problem: staff time is scarce, qualifications decay, new support needs can appear before anyone is prepared for them, and training consumes the same hours needed by current students.

By Carlos Eduardo Sanoja, Oscar Enrique Moreno Mayz

benchmarks safety

arXiv Machine Learning

Aug 4

Inferring Relative Consequences of Mechanical Ventilation from Observational Data Using Game-Based Comparisons

arXiv:2510. 15127v3 Announce Type: replace-cross Abstract: Identifying the effects of mechanical ventilation (MV) protocols in critical care requires analyzing data from heterogeneous patient-ventilator systems in the clinical decision-making environment.

By David J. Albers, Tell D. Bennett, Jana de Wiljes, George Hripcsak, Bradford J. Smith, Peter D. Sottile, J. N. Stroh

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 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 Machine Learning

5d ago

Chance-constrained selection of sequential intervention strategies from counterfactual estimates

arXiv:2608. 13209v1 Announce Type: cross Abstract: Many operational decisions are sequences of interventions under a cumulative resource limit, such as a maintenance schedule within a crew-hour budget.

By Minkyoung Kim, Beakcheol Jang

safety

arXiv Machine Learning

Jun 19

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.

By Thomas Frost, Steve Harris

reinforcement-learning

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

Jul 30

Early Verdicts, Better Budgets: Sequential Adaptive Rollout Allocation for Compute-Efficient RLVR

arXiv:2607. 26253v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) is bottlenecked by rollout generation, yet many sampled prompts produce saturated groups (all responses correct or all incorrect) whose zero reward variance yields no policy-gradient signal.

By Pixel Nomand, Elena Voss, Marcus Hale, Sofia Reyes

reinforcement-learning

arXiv AI

Jun 30

MedEvoEval: Evaluating Continual Evolution of Doctor Agents through Simulated Clinical Episodes

arXiv:2606. 28900v1 Announce Type: new Abstract: Doctor agents are moving beyond single-turn answer generation toward evolving clinical decision systems.

By Hui Zhang

agents benchmarks

arXiv Machine Learning

Jun 4

VentAgent: When LLMs Learn to Breathe -- Multi-Objective Arbitration for ARDS Ventilation

arXiv:2606. 04632v1 Announce Type: new Abstract: Mechanical ventilation for Acute Respiratory Distress Syndrome (ARDS) requires balancing competing physiological goals, including oxygenation, lung protection, and acid-base homeostasis.

By Teqi Hao, Yuxuan Fu, Xiaoyu Tan, Shaojie Shi, Bohao Lv, Yinghui Xu, Xihe Qiu

llms agents reinforcement-learning benchmarks safety

arXiv Machine Learning

Jun 18

Context-Aware Optimization of Follow-Up Intervals for Type 2 Diabetes Care Using Markov Decision Processes

arXiv:2606. 19092v1 Announce Type: cross Abstract: Chronic disease management relies on regular patient-provider interactions to follow-up on disease progression and control.

By Parisa Lotfibagha, Kristen Miller, William J. Gallagher, Elizabeth B. Selden, Muge Capan

reinforcement-learning benchmarks

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