Understanding the Potentiality of Artificial Intelligence in Psychological Disorders Detection and Diagnostics

Krishanu Aich, Sukrit Kashyap, Konika Tyagi, Ishika Verma, Abhimanyu Chauhan, Chakresh Kumar Jain
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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.
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了解人工智能在心理障碍检测和诊断中的潜力
如今,由于引入了数字工具来治疗心理健康疾病,心理保健的评估、预测、治疗或医疗的进步已经开始使用人工智能(AI)技术,尤其是机器学习。在心理健康治疗方面,人工智能技术的现在和未来都蕴含着巨大的前景和潜在的危险。在当前的全球形势下,临床抑郁症、一般焦虑症、创伤后应激障碍或躁郁症等心理疾病的报告率令人震惊。然而,从人工智能的角度来看,我们看到了诊断和早期检测这类疾病的转变趋势。深度学习模型和机器学习的力量,包括支持向量机(SVM)、逻辑回归、决策树、随机森林,以及自然语言处理、神经网络等深度学习模型,一直致力于帮助专家建立相关的技术和预测模型。本文以鹰眼视角介绍了这一领域正在开展的工作。文章重点介绍了上述四大心理疾病、人工智能技术及其在疾病中的应用现状,并探讨了人工智能如何在考虑其固有挑战、局限性和道德因素的同时,对患者护理起到补充作用。人工智能是一个迅速崛起且不断扩展的研究领域,它为医疗保健领域带来了许多前景,同时也带来了挑战。
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