关键词: 机器学习, 医学教育, 临床数据

Abstract: Machine learning is rapidly evolving into clinical artificial intelligence (AI) systems that can assist specific medical decisions. However, at present, machine learning faces the limitation factors such as high heterogeneity of clinical data and difficulty in data analysis of clinical tasks. Future, "intelligent" doctors should dominate innovations in medicine and AI engineering around clinical goals and clinical data. Therefore, in the form of medical student internship or resident training case learning, adding practical training such as estimation of the minimum sample size required for machine learning and clinical interpretation of advanced characteristics of data is conducive to cultivating medical students with clinical thinking of computer-based diagnosis and treatment and innovating a more efficient intelligent medical decision-making system.

Key words: Machine learning, Medical education, Clinical data