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Application of Neural Network and Machine Learning in Mental Health Diagnosis
| Content Provider | Scilit |
|---|---|
| Author | Das, Aniruddha Prasad, Enakshie Nair, Sindhu |
| Copyright Year | 2021 |
| Description | This chapter discusses the approach toward detecting negative emotions has been explored, i.e., depression using a CNN model. The standard questionnaire approaches, for example, Beck's depression inventory, are commonly used but work as preliminary tools of diagnosis due to their limitations. The chapter aim to utilize the capabilities of text-based emotion detection for the purpose of analyzing the emotional state of a patient suffering from mental health-related disorders. Based on the currently available datasets, certain attempts at mental health diagnosis have been made via these different approaches. In the International Health Conference of 1946, the representatives of 61 states decided that health is a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity. Numerous measures are used by mental health specialists to procure preliminary findings that may serve as an indication of depression. Book Name: Design of Intelligent Applications Using Machine Learning and Deep Learning Techniques |
| Related Links | https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.1201/9781003133681-6&type=chapterpdf |
| DOI | 10.1201/9781003133681-6 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2021-07-07 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Design of Intelligent Applications Using Machine Learning and Deep Learning Techniques Psychology Mental Health Neural Emotions Diagnosis Preliminary Detection |
| Content Type | Text |
| Resource Type | Chapter |
