Reinforcement Learning (RL) is a machine learning paradigm that enhances clinical decision-making for healthcare professionals by addressing uncertainties and optimizing sequential treatment strategies. RL leverages patient-data to create personalized treatment plans, improving outcomes and resource efficiency. This review introduces RL to a clinical audience, exploring core concepts, potential applications, and challenges in integrating RL into clinical practice, offering insights into efficient, personalized, and effective patient care.

中文翻译：

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面向临床医生的医学强化学习入门

强化学习 （RL） 是一种机器学习范式，它通过解决不确定性和优化序贯治疗策略来增强医疗保健专业人员的临床决策。RL 利用患者数据创建个性化的治疗计划，从而提高结果和资源效率。这篇综述向临床受众介绍了 RL，探讨了将 RL 整合到临床实践中的核心概念、潜在应用和挑战，为高效、个性化和有效的患者护理提供了见解。