论文标题
医疗保健的概率机器学习
Probabilistic Machine Learning for Healthcare
论文作者
论文摘要
机器学习可用于理解医疗保健数据。概率机器学习模型有助于提供医疗保健中观察到的数据的完整图片。在这篇综述中，我们研究了概率机器学习如何推进医疗保健。我们考虑了预测模型构建管道中的挑战，其中概率模型可能是有益的，包括校准和缺少数据。除了预测模型之外，我们还研究了概率机器学习模型在表型中的实用性，在临床用例的生成模型和增强学习中。
Machine learning can be used to make sense of healthcare data. Probabilistic machine learning models help provide a complete picture of observed data in healthcare. In this review, we examine how probabilistic machine learning can advance healthcare. We consider challenges in the predictive model building pipeline where probabilistic models can be beneficial including calibration and missing data. Beyond predictive models, we also investigate the utility of probabilistic machine learning models in phenotyping, in generative models for clinical use cases, and in reinforcement learning.
