Healthcare Recommendation System For Depression Using Machine Learning Algorithms
Jerusha S
, Deepika R , Hemalatha G , Keerthiga D
depression, random forest, knn, logistic regression, quality of life
Over the years, stress and anxiety causes major effects in people’s minds worldwide. New technological advancements are changing the future of the healthcare system. Lifestyle is something which defines an individual the best. Lifestyle including factors like income, age group, marital status, child, alcohol consumption and many more affect the quality of life of an individual. Identification of factors that are responsible for causing depression may lead to new experiments and treatments. Because depression as a disease is becoming a leading community health concern worldwide. NHANES is a program of studies designed to assess the health and nutritional status of adults and children. NHANES conducted a survey for analyzing depression and more than 1200 responses were recorded. These responses are used for training the model and for predicting the depression level. Using machine learning techniques this project presents a complete methodological framework to process and explore the heterogeneous data and to better understand the association between factors related to quality of life and depression. With the identified features, different models were chosen and trained accordingly. Random Forest, Logistic Regression and KNN have been chosen. By evaluating the results of various ML algorithms, Random Forest Classifier outperformed all other algorithms in predicting the levels of depression. The RF based prediction model is more accurate and informative in predicting. The final outcome received was 81.22%. Then, according to the level of depression, a recommendation will be given for future therapy. The recommendation will also consider the parameters responsible for the depression. This will help in assistance to other researchers and clinicians with the recognition of risk related to depression and other psychological disorders.
"Healthcare Recommendation System For Depression Using Machine Learning Algorithms", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.9, Issue 1, page no.597 - 604, January-2024, Available :https://ijsdr.org/papers/IJSDR2401086.pdf
Volume 9
Issue 1,
January-2024
Pages : 597 - 604
Paper Reg. ID: IJSDR_209931
Published Paper Id: IJSDR2401086
Downloads: 000347213
Research Area: Engineering
Country: Chennai, Tamilnadu, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
