Subphenotyping depression using machine learning and electronic health records

• 主要な著者: Zhenxing Xu (著者), Fei Wang (著者), Prakash Adekkanattu (著者), Budhaditya Bose (著者), Veer Vekaria (著者), Pascal Brandt (著者), Guoqian Jiang (著者), Richard C. Kiefer (著者), Yuan Luo (著者), Jennifer A. Pacheco (著者), Luke V. Rasmussen (著者), Jie Xu (著者), George Alexopoulos (著者), Jyotishman Pathak (著者)
• フォーマット: 図書
• 出版事項: Wiley, 2020-10-01T00:00:00Z.
• 主題: article
• オンライン･アクセス: Connect to this object online.

Abstract Objective To identify depression subphenotypes from Electronic Health Records (EHRs) using machine learning methods, and analyze their characteristics with respect to patient demographics, comorbidities, and medications. Materials and Methods Using EHRs from the INSIGHT Clinical Research Ne...