Bias Reducing Multitask Learning on Mental Health Prediction

• Published in: International Conference on Affective Computing and Intelligent Interaction and workshops pp. 1 - 8
• Main Authors: Zanna, Khadija, Sridhar, Kusha, Yu, Han, Sano, Akane
• Format: Conference Proceeding
• Language: English
• Published: IEEE 18.10.2022
• Subjects: Analytical models; Anxiety disorders; bias; epistemic uncertainty; fairness metric; Machine learning; Mental health; Monte-Carlo dropout; multi-task learning; Physiology; Predictive models; protected label; Uncertainty
• ISSN: 2156-8111
• DOI: 10.1109/ACII55700.2022.9953850

There has been an increase in research in developing machine learning models for mental health detection or prediction in recent years due to increased mental health issues in society. Effective use of mental health prediction or detection models can help mental health practitioners re-define mental...