MentalAId: an improved DenseNet model to assist scalable psychosis assessment.

Journal: BMC psychiatry
Published Date: Jul 30, 2025

Abstract

BACKGROUND: The escalating mental health crisis during and post-COVID-19 underscores the urgent need for scalable, timely, cost-effective assessment solutions for general psychotic disorders. Regretfully, traditional symptom-based, one-to-one assessment face inherent limitations in large-scale and longitudinal screening, likely delaying early intervention.

Authors

  • Muxi Li
    State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian, 361102, P R China.
  • Farong Liu
    College of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao, 266061, China.
  • Fei Du
    State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian, China.
  • Guolin Hong
    Department of Laboratory Medicine, Xiamen Key Laboratory of Genetic Testing, the First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, 361003, Fujian, China. xmhgl9899@xmu.edu.cn.
  • Qing Hu
    School of Mathematics and Statistics, Lanzhou University, Lanzhou, 730000, China. Electronic address: huq21@lzu.edu.cn.
  • Zhi-Liang Ji
    State Key Laboratory of Stress Cell Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361102, P.R. China The Key Laboratory for Chemical Biology of Fujian Province, Xiamen University, Xiamen, Fujian 361005, P.R. China appo@xmu.edu.cn.
  • Pan You
    Xiamen Xianyue Hospital, Xiamen, Fujian, China.

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