基础医学与临床 ›› 2021, Vol. 41 ›› Issue (7): 1071-1075.

• 医学教育 • 上一篇    下一篇

培养医学生机器学习的实践素养

刘大路,李静   

  1. 空军军医大学
  • 收稿日期:2020-10-28 修回日期:2021-04-06 出版日期:2021-07-05 发布日期:2021-06-17
  • 通讯作者: 李静 E-mail:jingli@fmmu.edu.cn
  • 基金资助:
    国家自然科学基金;陕西省自然科学基础研究计划

Cultivating practical literacy of machine learning for medical students

  • Received:2020-10-28 Revised:2021-04-06 Online:2021-07-05 Published:2021-06-17

摘要: 机器学习正快速发展为可辅助特定医学决策的临床人工智能系统。但是目前机器学习面临临床数据不均一性高、临床任务机器转化难度大等限制因素。未来“智能”医生应当主导围绕临床目标和临床数据的医学和智能工程的创新。因此,在医学生实习或住院医师培训中以案例学习的形式,加入对机器学习所需最小样本量的估算和数据高级特征的临床解读等素养的实践训练,有利于培养医学生具备智能辅助诊疗的临床思维,创新更高效的智能医学决策体系。

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

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