探索机器学习算法识别心力衰竭患者:托斯卡纳地区案例研究

Silvia Panicacci, M. Donati, L. Fanucci, I. Bellini, F. Profili, P. Francesconi
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引用次数: 1

摘要

心力衰竭患者已经成为医疗保健系统的一个重要挑战,因为他们代表了一个医疗、社会和经济问题。早期心力衰竭诊断对提高患者的生活质量和减少资源消耗非常有用,但对全科医生来说可能很复杂。数据挖掘和机器学习技术确实可以在这个领域提供帮助。本研究的目的是验证一些机器学习模型来识别心力衰竭患者,从管理数据开始,并使其透明和可解释。尽管缺乏临床数据,无法在意大利获得,但大多数用于心力衰竭患者的识别,结果可与最先进的模型相媲美,并且模型的性能优于托斯卡纳已经获得的性能。
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Exploring Machine Learning Algorithms to Identify Heart Failure Patients: the Tuscany Region Case Study
Heart failure patients have become an important challenge for the healthcare system, since they represent a medical, social and economic problem. Early heart failure diagnoses can be very useful to improve patients' quality of life and to reduce the resources consumption, but they can be complex for the general practitioners. Data mining and machine learning techniques can really help in this field. The aim of this study is to validate some machine learning models to identify heart failure patients, starting from administrative data, and to make them transparent and interpretable. Despite the lack of clinical data, not available in Italy, but the most employed for the identification of heart failure patients, the results are comparable with the state-of-the-art ones and the models outperform the performances already obtained in Tuscany.
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