Polycystic Ovary Syndrome Prediction [ML]

Chavan Ganesh Baban; Gonte Akanksha Vijay; Hole Swaranjali Shivaji; Khande Dnyaneshwari  Vikas; Khande Dnyaneshwari  Vikas

Polycystic Ovary Syndrome Prediction [ML]

November 2023

Vol-9, Issue-6

Paper ID: 22057

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Information Technology Engineering

Keywords

PCOS women's health male hormones infertility early detection machine learning feature selection Gaussian Naive Bayes (GNB) accuracy prolactin (PRL) blood pressure thyroid-stimulating hormone (TSH) pregnancy miscarriage intervention

Abstract

Polycystic Ovary Syndrome (PCOS) is a significant health risk for women during their reproductive years. The disorder is characterized mainly by higher levels of male hormones and androgens, which cause the formation of fluid-filled follicles in the ovaries, preventing regular egg release. PCOS can result in difficulties such as miscarriage, infertility, and pregnancy troubles. According to the most recent information, about 31.3% of women in Asia have PCOS, and sadly, 69% to 70% of these instances go misdiagnosed. Recognizing the critical need for research to enable early detection and intervention to prevent serious PCOS effects, our primary research objective is to develop a predictive model for PCOS implementing advanced machine learning techniques. To establish our predictive models, we use a collection of clinical and physical information from women. We provide a novel feature selection method based on an optimized chi-squared (CS-PCOS) mechanism to improve accuracy and efficacy. The Gaussian Naive Bayes (GNB) method emerges as the top-performing model, overcoming other machine learning models and state-of-the-art studies, due to the novel CS-PCOS feature selection technique. GNB provides exceptional results with 100% accuracy, precision, recall, and F1-scores while requiring only 0.002 seconds of calculating time. Our results highlight the importance of various dataset features such as , waist-hip ratio , prolactin (PRL), systolic and diastolic blood pressure, thyroid-stimulating hormone (TSH), relative risk of breaths (RR-breaths), and pregnancy in PCOS prediction. Using the GNB algorithm and these critical criteria, our work intends to aid the medical community in early PCOS detection, thereby reducing miscarriage occurrences and enabling earlier management for women suffering from this disorder.

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Author Information

#	Name	Institute / Affiliation
1	Chavan Ganesh Baban	SVPM COE Malegoan Bk
2	Gonte Akanksha Vijay	SVPM COE Malegoan Bk
3	Hole Swaranjali Shivaji	SVPM COE Malegoan Bk
4	Khande Dnyaneshwari Vikas	SVPM COE Malegoan Bk
5	Khande Dnyaneshwari Vikas	SVPM COE Malegoan Bk

How to Cite

Use the following formats to cite this article in your research.

APA Style

Baban, Chavan Ganesh, Vijay, Gonte Akanksha, Shivaji, Hole Swaranjali, Vikas, Khande Dnyaneshwari , & Vikas, Khande Dnyaneshwari (2023). Polycystic Ovary Syndrome Prediction [ML]. International Journal of Advance Research and Innovative Ideas In Education, 9(6), 735-742.

MLA Style

Baban, Chavan Ganesh, et al. "Polycystic Ovary Syndrome Prediction [ML]." International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 6, 2023, pp. 735-742.

IEEE Style

Chavan Ganesh Baban, Gonte Akanksha Vijay, Hole Swaranjali Shivaji, Khande Dnyaneshwari Vikas, and Khande Dnyaneshwari Vikas, "Polycystic Ovary Syndrome Prediction [ML]," International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 6, pp. 735-742, 2023.

Vancouver Style

Baban Chavan Ganesh, Vijay Gonte Akanksha, Shivaji Hole Swaranjali, Vikas Khande Dnyaneshwari , Vikas Khande Dnyaneshwari . Polycystic Ovary Syndrome Prediction [ML]. International Journal of Advance Research and Innovative Ideas In Education. 2023;9(6):735-742.

Harvard Style

Baban, Chavan Ganesh, Vijay, Gonte Akanksha, Shivaji, Hole Swaranjali, Vikas, Khande Dnyaneshwari , & Vikas, Khande Dnyaneshwari (2023) 'Polycystic Ovary Syndrome Prediction [ML]', International Journal of Advance Research and Innovative Ideas In Education, 9(6), pp. 735-742.

Chicago Style

Baban, Chavan Ganesh, et al. "Polycystic Ovary Syndrome Prediction [ML]." International Journal of Advance Research and Innovative Ideas In Education 9, no. 6 (2023): 735-742.

Turabian Style

Baban, Chavan Ganesh, et al. "Polycystic Ovary Syndrome Prediction [ML]." International Journal of Advance Research and Innovative Ideas In Education 9, no. 6 (2023): 735-742.