JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE) ›› 2022, Vol. 42 ›› Issue (1): 124-129.doi: 10.3969/j.issn.1674-8115.2022.01.019

• Review • Previous Articles    

Application progress of machine learning in the study of facial features of patients with depression

Xin LI(), Qing FAN()   

  1. Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
  • Received:2021-07-21 Online:2022-01-28 Published:2022-02-18
  • Contact: Qing FAN E-mail:lixin97vvv@163.com;fanqing_98@vip.sina.com
  • Supported by:
    Clinical Medicine Project of “Scientific and Technological Innovation Action Plan” of Shanghai Municipal Commission of Science and Technology(18411952000)

Abstract:

Major depressive disorder (MDD) is a mental illness that severely affects the quality of life, accompanied by changes in facial expressions and other behaviors. The current diagnosis for MDD mainly relies on self-reports and observations from doctors, which has subjective errors. There is a lack of objective and effective automated MDD detection methods. Facial expressions are important nonverbal behaviors, and the researchers have begun to use facial features to assist in identifying and diagnosing depression. As the core of artificial intelligence, machine learning has outstanding advantages in image feature extraction and classification. Taking IEEE Xplore database as the data source, this article sorts out the researches on the facial features of MDD patients based on machine learning from 2016 to 2021, and prospects the future research directions, to provide reference for clinical intelligent diagnosis and tracking of MDD in the future.

Key words: major depressive disorder (MDD), machine learning, facial feature, facial expression

CLC Number: