Schizophrenia: A Survey of Artificial Intelligence Techniques Applied to Detection and Classification

• Main Authors: Joel Weijia Lai, Candice Ke En Ang, U. Rajendra Acharya, Kang Hao Cheong
• Format: Article
• Language: English
• Published: MDPI AG 2021-06-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: artificial intelligence; machine Learning; mental health; schizophrenia
• Online Access: https://www.mdpi.com/1660-4601/18/11/6099

Artificial Intelligence in healthcare employs machine learning algorithms to emulate human cognition in the analysis of complicated or large sets of data. Specifically, artificial intelligence taps on the ability of computer algorithms and software with allowable thresholds to make deterministic approximate conclusions. In comparison to traditional technologies in healthcare, artificial intelligence enhances the process of data analysis without the need for human input, producing nearly equally reliable, well defined output. Schizophrenia is a chronic mental health condition that affects millions worldwide, with impairment in thinking and behaviour that may be significantly disabling to daily living. Multiple artificial intelligence and machine learning algorithms have been utilized to analyze the different components of schizophrenia, such as in prediction of disease, and assessment of current prevention methods. These are carried out in hope of assisting with diagnosis and provision of viable options for individuals affected. In this paper, we review the progress of the use of artificial intelligence in schizophrenia.