Open Access

ARTICLE

Automatic Diagnosis of Polycystic Ovarian Syndrome Using Wrapper Methodology with Deep Learning Techniques

Mohamed Abouhawwash^1,2, S. Sridevi³, Suma Christal Mary Sundararajan⁴, Rohit Pachlor⁵, Faten Khalid Karim⁶, Doaa Sami Khafaga^6,*

1 Department of Mathematics, Faculty of Science, Mansoura University, Mansoura, 35516, Egypt
2 Department of Computational Mathematics, Science, and Engineering (CMSE), College of Engineering, Michigan State University, East Lansing, MI, 48824, USA
3 Sri Ramachandra Faculty of Engineering & Technology, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, 600116, India
4 Department of Information Technology, Panimalar Institute of Technology, Chennai, 600123, India
5 Department of Computer Science and Engineering, School of Engineering, MIT Art, Design and Technology University, Pune, 412201, India
6 Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourahbint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia

* Corresponding Author: Doaa Sami Khafaga. Email: