Classification of Polycystic Ovary Syndrome (PCOS) data using machine learning algorithms
Pages : 1124-1127
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Abstract
In detected in women or girls in their reproductive age. PCOS is caused due to imbalance in the hormone level. PCOS lead to irregularity in menstrual periods. The irregular periods further cause formation of cysts (follicles) in either or both ovaries as well as infertility. PCOS symptoms include abnormal periods, disturbance in androgen levels, ovaries having cysts, increased BMI and some other abnormalities in hormone level of LH, FSH, DHEAS, Fasting insulin and Fasting blood sugar. This disease should be detected and prevented as early as possible. An intelligent software will help the health care providers to examine the patients and diagnose the risk of PCOS. This paper is work in progress of our proposed research to detect PCOS. Various machine learning algorithms are implemented on the dataset.
Keywords: Ppolycystic ovary syndrome, sonography, machine learning, classification.