arXiv Machine Learning July 21, 2026 By Divyansh Chawla, Anshu Garg, Isshaan Singh

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

Read the original on arXiv Machine Learning →

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.

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arXiv Machine Learning

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

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arXiv AI

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

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reinforcement-learning safety

arXiv AI

Jun 16

Medical world models: representing medical states, modelling clinical dynamics and guiding intervention policies

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arXiv Machine Learning

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Enhancing Q-Value Updates in Deep Q-Learning via Successor-State Prediction

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arXiv AI

Jun 10

Belief-Space Control for Personalized Cancer Treatment via Active Inference

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By Deniz Sargun, H. Bugra Tulay, C. Emre Koksal

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arXiv AI

Jun 10

Model-Based Reinforcement Learning in Discrete-Action Non-Markovian Reward Decision Processes

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