Mental Health Prediction Using Machine Learning: Taxonomy, Applications, and Challenges

Jetli Chung,Jason Teo,Aniello Minutolo

doi:10.1155/2022/9970363

Abstract

The increase of mental health problems and the need for effective medical health care have led to an investigation of machine learning that can be applied in mental health problems. This paper presents a recent systematic review of machine learning approaches in predicting mental health problems. Furthermore, we will discuss the challenges, limitations, and future directions for the application of machine learning in the mental health field. We collect research articles and studies that are related to the machine learning approaches in predicting mental health problems by searching reliable databases. Moreover, we adhere to the PRISMA methodology in conducting this systematic review. We include a total of 30 research articles in this review after the screening and identification processes. Then, we categorize the collected research articles based on the mental health problems such as schizophrenia, bipolar disorder, anxiety and depression, posttraumatic stress disorder, and mental health problems among children. Discussing the findings, we reflect on the challenges and limitations faced by the researchers on machine learning in mental health problems. Additionally, we provide concrete recommendations on the potential future research and development of applying machine learning in the mental health field.

Highlights

Mental illness is a health problem that undoubtedly impacts emotions, reasoning, and social interaction of a person.ese issues have shown that mental illness gives serious consequences across societies and demands new strategies for prevention and intervention
The documents and information related to the machine learning approaches that have been used by the researchers to conduct a prediction or diagnosis for mental health problems will be reviewed and discussed
The performance of the machine learning algorithms used will be evaluated and analyzed. e mental health problems will be categorized into several mental health disorders such as schizophrenia, anxiety and depression, bipolar disorder, posttraumatic stress disorder, and children’s mental health problems

Summary

Introduction

Mental illness is a health problem that undoubtedly impacts emotions, reasoning, and social interaction of a person. Ese issues have shown that mental illness gives serious consequences across societies and demands new strategies for prevention and intervention. To accomplish these strategies, early detection of mental health is an essential procedure. Mental illness is usually diagnosed based on the individual self-report that requires questionnaires designed for the detection of the specific patterns of feeling or social interactions [2]. It is believed to be a significantly useful tool to help in predicting mental health. It is allowing many researchers to acquire important information from the data, provide personalized experiences, and develop automated intelligent systems [4]

Methods

Results

Conclusion