A novel interpretable machine learning framework for predicting postpartum depression: a SHAP-based analysis of maternal and infant health indicators - Top-Institutions - MDSpire

A novel interpretable machine learning framework for predicting postpartum depression: a SHAP-based analysis of maternal and infant health indicators

  • By

  • Feng Lv

  • Shufang Li

  • Xiang Yuan

  • Yan Ma

  • Tingyang Huang

  • Jiaan Xie

  • Baoying Feng

  • Jianqiu Zheng

  • Jifeng Feng

  • Jianlan Mo

  • July 8, 2026

  • 0 min

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Top Institutions in Obgyn

Brief introduction explaining scope and methodology.

  • #1

    Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region
    Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region

    Nanning, Guangxi

    Key Differentiators

    • Maternal and Child Health

  • #2

    Cedars-Sinai
    Cedars-Sinai

    Los Angeles, California

    Key Differentiators

    • Psychiatry
    • Artificial Intelligence Research

  • #3

    NewYork-Presbyterian Hospital
    NewYork-Presbyterian Hospital

    New York, New York

    Key Differentiators

    • Psychiatry
    • Maternal Health

Original Source(s)

A novel interpretable machine learning framework for predicting postpartum depression: a SHAP-based analysis of maternal and infant health indicators

  • by Feng Lv, Shufang Li, Xiang Yuan, Yan Ma, Tingyang Huang, Jiaan Xie, Baoying Feng, Jianqiu Zheng, Jifeng Feng, Jianlan Mo

  • July 8, 2026

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