Using Data Mining to Predict Possible Future Depression Cases

Kevin Daimi • Shadi Banitaan
Journal article International Journal of Public Health Science • December 2014

Abstract

Depression is a disorder characterized by misery and gloominess felt over a period of time. Some symptoms of depression overlap with somatic illnesses implying considerable difficulty in diagnosing it. This paper contributes to its diagnosis through the application of data mining, namely classification, to predict patients who will most likely develop depression or are currently suffering from depression. Synthetic data is used for this study. To acquire the results, the popular suite of machine learning software, WEKA, is used.

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Journal

International Journal of Public Health Science

The International Journal of Public Health Science (IJPHS) is an interdisciplinary and peer-revie... see more