A Study and Prediction of Psychological Disorders Through Machine Learning

Year : 2024 | Volume : 02 | Issue : 02 | Page : 32 38
    By

    Sandeep Mishra,

  • Garima Sharma,

  • Chirag Rawat,

  • Khushi Mishra,

  • Krishna Aggarwal,

  • Kaustubh Kumar Shukla,

  1. Assistant Professor, Department of Computer Science and Engineering, Dronacharya Group of Institutions, Greater Noida, Uttar Pradesh, India
  2. Student, Department of Computer Science and Engineering, Dronacharya Group of Institutions, Greater Noida, Uttar Pradesh, India
  3. Student, Department of Computer Science and Engineering, Dronacharya Group of Institutions, Greater Noida, Uttar Pradesh, India
  4. Student, Department of Computer Science and Engineering, Dronacharya Group of Institutions, Greater Noida, Uttar Pradesh, India
  5. Student, Department of Computer Science and Engineering, Dronacharya Group of Institutions, Greater Noida, Uttar Pradesh, India
  6. Associate Professor, Department of Electronics and Communication Engineering, Dronacharya Group of Institutions, Greater Noida, Uttar Pradesh, India

Abstract

Physical illness is very much visible but not psychological illness therefore, it requires more attention and care. Psychological disorders also known as psychiatric disorders refer to a wide range of conditions affecting a person’s thought process, leading to significant changes in the behavior of an individual. The most prevalent psychological disorders include depression, anxiety disorders, and post-traumatic stress disorder (PTSD). Symptoms of psychological disorders vary greatly but include common symptoms like changes in mood and cognition. These disorders undermine an individual ability to function effectively in daily life, impacting their well-being. An individual’s behavior and way of thinking are impacted by psychological disorders such as PTSD, anxiety, and depression, which affect their general well-being. They need the right medication, counseling, and assistance. Algorithms for machine learning are essential for both diagnosing and treating these conditions. Through the analysis of vast datasets, the study looks into two widely used supervised learning models, random forest, and decision trees, which can accurately detect and comprehend the origin and course of various conditions. By using these models in healthcare, professionals will be better able to identify these conditions and understand their underlying causes.

Keywords: Psychiatric disorders, random forest, decision trees, supervised, anxiety, depression, stress, treatment, prediction, algorithms

[This article belongs to International Journal of Algorithms Design and Analysis Review ]

How to cite this article:
Sandeep Mishra, Garima Sharma, Chirag Rawat, Khushi Mishra, Krishna Aggarwal, Kaustubh Kumar Shukla. A Study and Prediction of Psychological Disorders Through Machine Learning. International Journal of Algorithms Design and Analysis Review. 2024; 02(02):32-38.
How to cite this URL:
Sandeep Mishra, Garima Sharma, Chirag Rawat, Khushi Mishra, Krishna Aggarwal, Kaustubh Kumar Shukla. A Study and Prediction of Psychological Disorders Through Machine Learning. International Journal of Algorithms Design and Analysis Review. 2024; 02(02):32-38. Available from: https://journals.stmjournals.com/ijadar/article=2024/view=179841


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Regular Issue Subscription Review Article
Volume 02
Issue 02
Received 19/10/2024
Accepted 22/10/2024
Published 25/10/2024
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