click here to download project abstract
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ABSTRACT
Polycystic Ovary Syndrome or PCOS is an endocrine disorder that occurs in women of
reproductive age. The condition once detected cannot be cured but treatment can help relieve its
effects.
The exact cause of PCOS is still unknown but there are certain factors that portray the risk of
getting PCOS. The factors that result in this syndrome are obesity, insulin resistance, blood
pressure, depression, inflammation. The symptoms include: hirsutism, Oligo-ovulation, acne, heavy
bleeding, skin darkening. Using the causes and symptoms, a model is prepared in order to accept
them as features and outputs the presence or absence of this condition. The machine learning
models used for supervised classification are Logistic Regression. The reason behind building
multiple models is to find out the best one for the given dataset, in the known scope of knowledge
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web- flask server
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access to all public
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refer the nearest gynecologist
