Investigation of Polycystic Ovary Syndrome (PCOS) Diagnosis Using Machine Learning Approaches-Reference-Cited by-同舟云学术

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Investigation of Polycystic Ovary Syndrome (PCOS) Diagnosis Using Machine Learning Approaches

Published:2023-12-09 Issue: Volume:31 Page:1-6
ISSN:
Container-title:2023 5th International Conference on Sustainable Technologies for Industry 5.0 (STI)
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Author:

Sultan Bin Habib Al Zadid¹,Bin Syed Md Asif²,Islam Md. Ekramul³,Tasnim Tanpia⁴

Affiliation:

1. West Virginia University,Lane Department of Computer Science and Electrical Engineering,Morgantown,WV,USA,26506

2. West Virginia University,Department of Industrial and Management Systems Engineering,Morgantown,WV,USA,26506

3. Stamford University Bangladesh,Department of Computer Science & Engineering,Dhaka,Bangladesh,1217

4. Green University of Bangladesh,Department of Computer Science and Engineering,Narayanganj, Dhaka,Bangladesh,1461

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10464389/10464391/10465079.pdf?arnumber=10465079

Reference27 articles.

1. Hyperandrogenism in polycystic ovarian syndrome and role of CYP gene variants: a review

2. PCOS Forum: research in polycystic ovary syndrome today and tomorrow

3. Current Management of Polycystic Ovary Syndrome: From Bench to Bedside

4. An extended machine learning technique for polycystic ovary syndrome detection using ovary ultrasound image

5. Particle Swarm Optimization on follicles segmentation to support PCOS detection

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