Current Volume 8
AI in Mental Health: Predictive Analytics for Early Detection and Intervention in Psychiatric Disorders
Abstract
Artificial intelligence (AI) technology proves useful to mental healthcare through predictive analytics, which identifies early-stage psychiatric disorders. AI uses machine learning algorithms to examine large volumes of clinical data that reveal recognizable indicators of depression, anxiety, and schizophrenia before professional diagnosis. The timely identification through early detection enables medical professionals to start proper treatments, increasing favorable treatment results and lowering long-term medical expenses. Numerous analytical techniques, such as data mining, natural processing, and deep learning methods, are used to model mental health disorders and subsequent risk potentials. Incorporating artificial intelligence into psychiatric care systems provides patients with custom-made therapeutic solutions and continuous health checks. This article examines existing AI implementations in psychiatry to demonstrate their effects while discussing obstacles alongside expected developments that will improve healthcare delivery for patients and mental health service operations.
Keywords
Artificial Intelligence, Machine Learning, Predictive Analytics, Mental Health, Early Detection, Psychiatric Disorders
Citations
IRE Journals:
Fnu Zartashea
"AI in Mental Health: Predictive Analytics for Early Detection and Intervention in Psychiatric Disorders" Iconic Research And Engineering Journals Volume 6 Issue 4 2022 Page 183-194
IEEE:
Fnu Zartashea
"AI in Mental Health: Predictive Analytics for Early Detection and Intervention in Psychiatric Disorders" Iconic Research And Engineering Journals, 6(4)
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IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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