Article Open Access

A Comparative Study of Data Mining Models using Essential Metrics in the Prediction of the Relation Between Polycystic Ovary Syndrome and Postpartum Depression in Women

Arya P. Pillai, N.V. Chinnasamy

Abstract


Around the world today, personal health care is an unavoidable task to be done in human life. The vest emergence of medical science and medical technology is accelerating day by day. In many paradigms, information technology plays a vital role in comparing the past evidence with the present in the medical field and as a result, predictions will be outlined. Data mining and Data mining algorithms in medical care have a major role in improving personal care and in the overall healthcare system. Women with PCOS are more reasonably experience several pregnancy issues, including diabetes mellitus, hypertension, anxiety and mood swings, which may sometimes lead to Postpartum Depression. This paper evaluates a few parameters related to health care and predicts the relationship between PCOS and PPD in women based on data mining approaches.


Keywords


PCOS, PPD, LR, Naïve Bayes, SVM

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DOI: https://doi.org/10.52088/ijesty.v5i2.1364

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International Journal of Engineering, Science, and Information Technology (IJESTY) eISSN 2775-2674