Artificial intelligence (AI) and machine learning (ML) methods are currently widely employed in medicine and healthcare. A PubMed search returns more than 100,000 articles on these topics published between 2018 and 2022 alone. Notwithstanding several recent reviews in various subfields of AI and ML in medicine, we have yet to see a comprehensive review around the methods’ use in longitudinal analysis and prediction of an individual patient's health status within a personalized disease pathway. This review seeks to fill that gap. After an overview of the AI and ML methods employed in this field and of specific medical applications of models of this type, the review discusses the strengths and limitations of current studies and looks ahead to future strands of research in this field. We aim to enable interested readers to gain a detailed impression of the research currently available and accordingly plan future work around predictive models for deterioration in health status.

中文翻译：

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健康恶化的预测模型：了解个性化医疗的疾病途径

人工智能（AI）和机器学习（ML）方法目前广泛应用于医学和医疗保健领域。仅 2018 年至 2022 年期间，PubMed 搜索就返回了超过 100,000 篇关于这些主题的文章。尽管最近对医学中人工智能和机器学习的各个子领域进行了一些综述，但我们尚未看到围绕这些方法在个性化疾病路径中纵向分析和预测个体患者健康状况的使用进行全面综述。本次审查旨在填补这一空白。在概述了该领域采用的人工智能和机器学习方法以及此类模型的具体医学应用之后，该综述讨论了当前研究的优势和局限性，并展望了该领域的未来研究方向。我们的目标是使感兴趣的读者能够详细了解当前可用的研究，并相应地围绕健康状况恶化的预测模型规划未来的工作。