{"title":"Understanding the Potentiality of Artificial Intelligence in Psychological Disorders Detection and Diagnostics","authors":"Krishanu Aich, Sukrit Kashyap, Konika Tyagi, Ishika Verma, Abhimanyu Chauhan, Chakresh Kumar Jain","doi":"10.21926/obm.neurobiol.2304198","DOIUrl":null,"url":null,"abstract":"Today, the advancement of assessment, forecasting, and therapy or medical attention for psychological healthcare is already using artificial intelligence (AI) technology, particularly machine learning, due to the introduction of digital tools to treat mental health conditions. In mental health treatment, the present and the future of artificial intelligence technologies hold both enormous promises and potential dangers. With the current global scenario, psychological disorders like clinical depression, general anxiety disorder, post-traumatic stress disorder, or bipolar disorder are being reported at an alarming rate. Nonetheless, from the perspective of artificial intelligence, we see a shifting trend in diagnosing and early detection of such disorders. The deep learning models and power of machine learning, including Support Vector Machine (SVM), Logistic Regression, Decision Trees, Random Forest, and deep learning models like Natural Language Processing, Neural Networks, etc., have been committed to helping experts build techniques and prediction models for the same. This article presents an eagle-eye view of the work being done in this field. It focuses on the four major psychological disorders mentioned above, artificial intelligence technology and its current applications in diseases, and a discourse on how artificial intelligence can complement patient care while considering its inherent challenges, limitations, and moral considerations. Artificial intelligence is a rapidly emerging and continuously expanding field of research, which offers many prospects to the healthcare sector along with the challenges.","PeriodicalId":74334,"journal":{"name":"OBM neurobiology","volume":"24 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"OBM neurobiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21926/obm.neurobiol.2304198","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Today, the advancement of assessment, forecasting, and therapy or medical attention for psychological healthcare is already using artificial intelligence (AI) technology, particularly machine learning, due to the introduction of digital tools to treat mental health conditions. In mental health treatment, the present and the future of artificial intelligence technologies hold both enormous promises and potential dangers. With the current global scenario, psychological disorders like clinical depression, general anxiety disorder, post-traumatic stress disorder, or bipolar disorder are being reported at an alarming rate. Nonetheless, from the perspective of artificial intelligence, we see a shifting trend in diagnosing and early detection of such disorders. The deep learning models and power of machine learning, including Support Vector Machine (SVM), Logistic Regression, Decision Trees, Random Forest, and deep learning models like Natural Language Processing, Neural Networks, etc., have been committed to helping experts build techniques and prediction models for the same. This article presents an eagle-eye view of the work being done in this field. It focuses on the four major psychological disorders mentioned above, artificial intelligence technology and its current applications in diseases, and a discourse on how artificial intelligence can complement patient care while considering its inherent challenges, limitations, and moral considerations. Artificial intelligence is a rapidly emerging and continuously expanding field of research, which offers many prospects to the healthcare sector along with the challenges.