Comparison of Machine Learning Models in Predicting Mental Health Sequelae Following Concussion in Youth.

Journal: AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
Published Date: Jun 10, 2025

Abstract

Youth who experience concussions may be at greater risk for subsequent mental health challenges, making early detection crucial for timely intervention. This study utilized Bidirectional Long Short-Term Memory (BiLSTM) networks to predict mental health outcomes following concussion in youth and compared its performance to traditional models. We also examined whether incorporating social determinants of health (SDoH) improved predictive power, given the disproportionate impact of concussions and mental health issues on disadvantaged populations. We evaluated the models using accuracy, area under the curve (4UC) of the receiver operating characteristic (ROC), and other performance metrics. Our BiLSTM model with SDoH data achieved the highest accuracy (0.883) and 4UC-ROC score (0.892). Unlike traditional models, our approach provided real-time predictions at each visit within 12 months of the index concussion, aiding clinicians in making timely, visit-specific referrals for further treatment and interventions.

Authors

  • Jin Peng
    Institute for Emergency and Disaster Medicine, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, No. 32, Yi Huan Lu Xi Er Duan, Chengdu, Sichuan Province, China; Sino-Finnish Medical AI Research Center, No. 32, Yi Huan Lu Xi Er Duan, Chengdu, Sichuan Province, China; Department of Histology, Embryology and Neurobiology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, No. 17, People's South Road, Chengdu, Sichuan, China. Electronic address: admin@traumabank.org.
  • Jiayuan Chen
    Department of Environment Science, Shaanxi Normal University, Xi'an 710062, China.
  • Changchang Yin
    The Ohio State University, Columbus, OH, United States.
  • Ping Zhang
    Department of Computer Science and Engineering, The Ohio State University, USA.
  • Jingzhen Yang
    Department of Pediatrics, College of Medicine, The Ohio State University, Center for Injury Research and Policy, Abigail Wexner Research Institute at Nationwide Children's Hospital, 700 Children's Dr. RBIII-WB5403 Columbus, OH 43205, USA. Electronic address: ginger.yang@nationwidechildrens.org.

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