Comparative Analysis of Machine Learning Algorithms in Diagnosis of Polycystic Ovarian Syndrome

    September 2020 in “ International journal of computer applications ”
    Malik Mubasher Hassan, Tabasum Mirza
    Studysummary This study found that the Random Forest machine learning algorithm achieved the highest accuracy, 96%, in diagnosing Polycystic Ovarian Syndrome using patients' clinical data.
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    Research cited in this study 3

    1. Epidemiology, Diagnosis, and Management of Polycystic Ovary Syndrome Clinical epidemiology · 2013
    2. Polycystic Ovary Syndrome and Its Impact on Health Middle East Fertility Society Journal · 2010
    3. Polycystic Ovary Syndrome and Cardiovascular Disease: A Premature Association? Endocrine Reviews · 2003