Title: Depression prediction and therapy recommendation using machine learning technique

Authors: K.G. Saranya; C.H. Babitha Reddy; M. Bhavyasree; M. Rubika; E. Varsha

Addresses: Department of CSE, PSG College of Technology, Coimbatore-04, India ' Department of CSE, PSG College of Technology, Coimbatore-04, India ' Department of CSE, PSG College of Technology, Coimbatore-04, India ' Department of CSE, PSG College of Technology, Coimbatore-04, India ' Department of CSE, PSG College of Technology, Coimbatore-04, India

Abstract: The most common misconception around the world would be the definition of 'health'. A person is considered to be healthy as long as they are physically fine, but that is not true. A person's mental health is also equally important while considering a person's health status. This incomprehension towards mental health has taken lives of many people. Despite the government and many NGOs spreading awareness on mental health, there is still a lack of understanding of mental health symptoms, societal stigma, and proper resources and facilities prevent people from seeking help. Among the types of mental disorders, many psychiatrists have agreed that depression and addiction are the most common ones to cause a person's life. There are a couple of existing systems that aids in depression detection and therapy recommendation, but the major issue found in those systems would be inefficiency and high computational cost. In this paper work, a new approach has been proposed to identify depression using Reddit comments.

Keywords: bidirectional encoder representation transformer; BERT; collaborative filtering; cosine similarity.

DOI: 10.1504/IJCSYSE.2024.137475

International Journal of Computational Systems Engineering, 2024 Vol.8 No.1/2, pp.120 - 127

Received: 02 Sep 2022
Accepted: 18 Apr 2023
Published online: 19 Mar 2024 *

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