基于机器学习的心理障碍检测与分析综述

Ujjwal Bhushan, Srabanti Maji, Anil Kumar
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引用次数: 1

摘要

在现代,技术的进步创造了医疗部门发展的需要。因此,对各种心理障碍进行预测和分析,尽快找到治疗方法是至关重要的。因此,生物信息学需要与机器学习一起工作。本文探讨了各种机器学习技术及其用于预测和分析各种心理障碍的实现。这些机器学习技术包括各种方法。在这些研究论文的研究过程中,我们观察到,尽管在不同的数据集上使用了许多学习方法,但使用SVM、KNN和ANN技术获得了高精度的结果。本文概述了不同的机器学习技术如何用于预测和分析各种心理障碍。这里提到的研究工作描述了如何使用机器学习技术在各种数据集上实现有效和经济的结果,而不考虑内容,即图像,音频或文本形式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review on Detection and Analysis of Psychological Disorders Using Machine Learning
In modern times, advancement in technology has created a need for evolution in the medical sector. As a result, it is crucial to predict and analyze the various psychological disorders to find their treatment as soon as possible. Thus this evolved the need for Bioinformatics to work with machine learning. In this paper, explored the various machine learning techniques and their implementation for prediction and analysis of various psychological disorders. These machine learning techniques include various methods. During the study of these research papers, it has been observed that although many learning methods have been used on various datasets, high accurate results have been achieved using SVM, KNN and ANN techniques. This manuscript provides an overview of how different machine learning techniques used to predict and analyze various psychological disorders. The research work mentioned here depicts how machine learning techniques used to achieve effective and economic results on various datasets irrespective of content i.e. image, audio or text form.
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