Identifying clinical features associated with electroconvulsive therapy response in adolescents with major depressive disorder using machine learning - Top-Institutions - MDSpire

Identifying clinical features associated with electroconvulsive therapy response in adolescents with major depressive disorder using machine learning

  • By

  • Bingyang Zha

  • Linjie Li

  • Jinglan He

  • Jun Cao

  • Su Hong

  • Li Kuang

  • May 7, 2026

  • 0 min

Share

Top Institutions in Psychiatry

Brief introduction explaining scope and methodology.

  • #1

    The First Affiliated Hospital of Chongqing Medical University
    The First Affiliated Hospital of Chongqing Medical University

    Chongqing, Chongqing

    Key Differentiators

    • Psychiatry

  • #2

    Cedars-Sinai
    Cedars-Sinai

    Los Angeles, California

    Key Differentiators

    • Psychiatry
    • Artificial Intelligence in Medicine

Original Source(s)

Identifying clinical features associated with electroconvulsive therapy response in adolescents with major depressive disorder using machine learning

  • by Bingyang Zha, Linjie Li, Jinglan He, Jun Cao, Su Hong, Li Kuang

  • May 7, 2026

Related Content

Psychometric properties of the short Indonesian version of the Academic Stress Scale and descriptive analysis of academic-related stress among adolescent students

Astigmatism Up After COVID Restrictions

Researchers identified delayed corneal changes in schoolchildren that emerged after myopia rates had already increased during the pandemic.

Immersive clinical learning using simulation and its impact on academic performance, satisfaction, self-confidence, and anxiety among pediatric nursing students