An Improved Technique for Risk Prediction of Polycystic Ovary Syndrome (PCOS) Using Feature Selection and Machine Learning-Reference-Cited by-同舟云学术

An Improved Technique for Risk Prediction of Polycystic Ovary Syndrome (PCOS) Using Feature Selection and Machine Learning

Author:

Aggarwal Nitisha^ORCID,Shukla Unmesh^ORCID,Saxena Geetika Jain^ORCID,Kumar Manish,Bafila Anil Singh^ORCID,Singh Sanjeev^ORCID,Pundir Amit^ORCID

Publisher

Springer Nature Singapore

Link

Reference29 articles.

4. Barthelmess EK, Naz RK (2014) Polycystic ovary syndrome: current status and future perspective. Front Biosci (Elite Ed) 6:104–119

5. Kottarathil P (2020) Polycystic ovary syndrome (PCOS)—version 3. https://www.kaggle.com/prasoonkottarathil/polycystic-ovary-syndrome-pcos

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3. Utilizing deep learning techniques for detection of Polycystic Ovarian Syndrome using ovarian ultrasound image;2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES);2023-12-14