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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM12833

Prediction of Mental Health using Machine Learning Techniques

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM12833

Volume:

6 |

5 |

May 2022

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM12833

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SCS

Satvik Chandra Saxena

T

Tanmay

DCM

Dr. C. Malathy

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Abstract

Earlier prognosis of mental health problems enables professionals deal with early and improves life. Depression is one of the main causes of incapacity international. This text gives a top level view of AI and present day programs in health care, a review of the latest AI mental health research, and a dialogue of ways AI can enhance medical exercise while considering its contemporary obstacles, regions that require in addition research, and behavioral influences. About AI technology. Therefore, there may be an urgent need to deal with simple mental health issues in children, that could lead to extreme headaches, if not treated early. Device getting to know strategies are presently properly-perfect for studying medical records and diagnosing a trouble. Attributes are downgraded the use of the feature selection algorithms on top of the total characteristic facts set. The accuracy over the full set of attributes and the selected characteristic set within the diverse device getting to know algorithms are comparable. However, warning is needed to avoid over-decoding the preliminary effects, and more work is needed to shut the gap between AI in mental fitness studies and clinical care.

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Cite This Article

Satvik Chandra Saxena, Tanmay, Dr. C. Malathy, "Prediction of Mental Health using Machine Learning Techniques," International Journal of Scientific Research in Engineering and Management, vol. 6, no. 5, May 2022. https://doi.org/10.55041/IJSREM12833

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Publication Date

11/4/2022

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Double-Blind Peer Review

Review Rounds: 2

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5

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The authors declare no conflict of interest related to this research work.

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