• Aayushi Sinha

PCOS is characterized by the ovaries production of an abnormal number of androgens. These androgens can cause more problems with the women’s menstrual cycle.It explores the application of ML techniques to predict PCOD/PCOS, a binary classification problem, and presents a comprehensive literature survey on existing research in this domain. It has been identified as one of the major health issues among women that directly affects fertility during reproductive ages , affecting 1 in every 10 women.. The objective of this study is to statistically evaluate the metabolic and clinical features, using dimensionality reduction and principal component analysis, and compare the accuracy and F1-Score of different machine learning models

"Polycystic Ovarian Syndrome Prediction : A Machine Learning Approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 7, page no.f267-f269, July-2024, Available :http://www.jetir.org/papers/JETIR2407539.pdf

"Polycystic Ovarian Syndrome Prediction : A Machine Learning Approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 7, page no. ppf267-f269, July-2024, Available at : http://www.jetir.org/papers/JETIR2407539.pdf