ISSN 2394-5125
 
2021, Vol: 8, Issue: 8
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    REVIEW ON POLYCYSTIC OVARY SYNDROME DETECTION USING MACHINE LEARNING (2020)
    Prof. Bere Sachin Sukhadeo, Prof. Salunke Shrikant Dadasaheb, Prof. Kadam Swati Amol, Prof. Deokate Vasuda Balaso, Prof. Dhage Shrikant Narhari, Prof. Madane Tai Abaso
    JCR. 2020: 13159-13163

    Abstract

    Polycystic ovary syndrome among women of tine or above 16year age has been steadily increasing, necessitating accurate and early prediction methods. Machine Learning techniques have shown great potential in this area due to their capability to analyze huge of data and identify complex datasets. This research paper aims to review existing studies on the PCOS prediction with the help of Machine Learning(ML). PCOS is a common endocrine disorder in females at tine age, characterized by hormonal fluctuations and the increased level in male hormone and androgen.

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    Volume & Issue

    Volume 7 Issue-19

    Keywords

    PCOS, ML, SVM, Hormonal Fluctuations, androgen, Supervised, Data Sources
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