Medically-oriented design for explainable AI for stress prediction from physiological measurements.

Journal: BMC medical informatics and decision making
Published Date: Feb 11, 2022

Abstract

BACKGROUND: In the last decade, a lot of attention has been given to develop artificial intelligence (AI) solutions for mental health using machine learning. To build trust in AI applications, it is crucial for AI systems to provide for practitioners and patients the reasons behind the AI decisions. This is referred to as Explainable AI. While there has been significant progress in developing stress prediction models, little work has been done to develop explainable AI for mental health.

Authors

  • Dalia Jaber
    Electrical and Computer Engineering Department, American University of Beirut, Beirut, Lebanon. drj01@mail.aub.edu.
  • Hazem Hajj
    Pathfinding, Automation Technology and Analytics, Intel Corporation, Hillsboro, Oregon, USA.
  • Fadi Maalouf
    Department of Psychiatry, American University of Beirut, Beirut, Lebanon.
  • Wassim El-Hajj
    Computer Science Department, American University of Beirut, Beirut, Lebanon.

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