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A Real Time Analysis and Prediction of Mental Health Disorder Based on Machine Learning Technique

EasyChair Preprint no. 7702

7 pagesDate: April 2, 2022


Mental fitness is the aggregation of emotional, social and mental well being of a person. It impacts at the person’s thinking, appearing and feeling capability. Mental fitness is a degree of managing strain and selection making with each step-in life. There is a lot records to be had that we're now capable of collect records for intellectual fitness experts via way of means of making use of this method they may benefited to clinicians the possibility to customize the professional & capable of carry out their task in higher manner in. Machine getting to know algorithms should assist decide key behaviour biomarkers to useful resource intellectual fitness experts in identifying if a affected person is vulnerable to growing a selected intellectual fitness disorder. Additionally, the algorithms might also additionally help in monitoring effectiveness of a remedy plan. This paper evaluations approximately the software of ML to intellectual fitness prediction, which incorporates a number of advantages throughout the regions of prognosis, remedy and support, research, and medical administration. With the bulk of research diagnosed focusing at the detection and prognosis of intellectual fitness conditions.

Keyphrases: 1)Machine learning, 2)schzophrenia, 3)Depression

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Karnika Shrivastava and Prashant Richhariya and Anita Soni},
  title = {A Real Time Analysis and Prediction of Mental Health Disorder Based on Machine Learning Technique},
  howpublished = {EasyChair Preprint no. 7702},

  year = {EasyChair, 2022}}
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