Role of Machine Learning in the Analysis of Mental Health Data: An Empirical Approach
- Title
- Role of Machine Learning in the Analysis of Mental Health Data: An Empirical Approach
- Creator
- Hashmi S.G.; Shahi F.I.; Qidwai K.A.; Naser M.; Shafiuddin M.; Upreti K.
- Description
- As funding for mental health research has grown, so too has the body of knowledge about how best to address and alleviate issues related to mental health. However, there is still a lack of certainty and clarity on the precise causes of mental diseases. Discovery of new drugs, analysis of radiological data, forecasting of disease outbreaks, and the diagnosis of illnesses are just some of the medical applications of machine learning algorithms. Machine learning algorithms are commonly used to sift through the mountains of medical data. Since their performance has improved to the point where it can be relied upon, they are now used to aid in medical diagnosis. To assess and address the issues with mental health, numerous new approaches and algorithms had been devised. There are still a lot of issues that can be resolved. So the main purpose of this study is to examine the effectiveness of machine learning in mental health problems. For fulfilling this purpose, this study is descriptive in nature. Primary data is collected with the help of interview method in which 50 individuals suffering from mental illness were asked to answers some questions. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
- Source
- Lecture Notes in Networks and Systems, Vol-730 LNNS, pp. 513-522.
- Date
- 2023-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Machine learning; Mental health; Supervised learning; Unsupervised learning
- Coverage
- Hashmi S.G., Department of Computer Science, College of Computer Science and Information Technology, Jazan University, Jizan, Saudi Arabia; Shahi F.I., Deanship of E-Learning and Information Technology, Jazan University, Jazan, Saudi Arabia; Qidwai K.A., Department of Computer Science, College of Computer Science and Information Technology, Jazan University, Jizan, Saudi Arabia; Naser M., Deanship of E-Learning and Information Technology, Jazan University, Jazan, Saudi Arabia; Shafiuddin M., AFS Department, Oman College of Management and Technology, Halban, Oman; Upreti K., Department of Computer Science CHRIST (Deemed to be University), Delhi NCR, Ghaziabad, India
- Rights
- Restricted Access
- Relation
- ISSN: 23673370; ISBN: 978-981993962-6
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Hashmi S.G.; Shahi F.I.; Qidwai K.A.; Naser M.; Shafiuddin M.; Upreti K., “Role of Machine Learning in the Analysis of Mental Health Data: An Empirical Approach,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/19827.