A Research on Stress and Depression Detection
Yashwanth B
, Sushmitha Suresh , V Laxmi Priya , M Yasaswani , T Vyshnavi
Decision Trees, Logistic Regression, Machine Learning, Random Forest.
The accurate Identification of mental well-being and Stress plays Significant participation in a person's treatment, especially in the disease’s early stages, as there are chances of risk occurrence in person’s health. Mental Health and Stress can be diagnosed-but not predicted at its early stages, as prediction is only applicable before the disease manifests itself. Deep Learning (DL) has evolved into a common technique to facilitate the prompt identification of Mental Health and Stress. Here, we introduce prediction on Mental Health using RNN help researchers diagnose the disease at its early stages. The website collects the dataset of the people/patients. After the required training processes is done, it helps to predict the mental health and stress of the person/patient. Some general queries of the person’s/patient’s mental and physical health are required.
"A Research on Stress and Depression Detection", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.a283-a286, February-2024, Available :https://tijer.org/TIJER/papers/TIJER2402035.pdf
Volume 11
Issue 2,
February-2024
Pages : a283-a286
Paper Reg. ID: TIJER_151207
Published Paper Id: TIJER2402035
Downloads: 000282
Research Area: Humanities All
Country: Bangalore, karnataka, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
