• Pallavi Santha
• Manjunadhan murigeshan
• Divya Nagaraju
• Vishnuvardhan Vemuri
• Mohan Kumar Pilli

Polycystic ovary syndrome, is a prevalent endocrine disorder affecting women who are ready to procreate, distinguished by an overabundance of androgens, and presenting with symptoms such as acne, alopecia, hirsutism, hyperandrogenemia, and oligoovulation. It is a major contributor to female infertility, with an estimated 15% of women in this age group affected worldwide. PCOS has multifaceted implications, including metabolic issues like insulin resistance, obesity, and dyslipidemia, as well as reproductive challenges such as irregular menstrual cycles and subfertility. Additionally, the psychological impact of PCOS can lead to distress, anxiety, and depression. Management of PCOS requires a multidisciplinary approach encompassing lifestyle modifications, pharmacological interventions, and psychological support. Early diagnosis and individualized treatment are crucial to minimizing long-term complications and improving the quality of life for women with PCOS.

Polycystic Ovary Syndrome (PCOS), MobileNet Image Processing Techniques, Deep Learning, Convolutional Neural Network (CNN), Ultrasound Images, Image Classification, Detection, Diagnosis, Automated Medical Image Analysis

"Polycystic Ovary Syndrome detection using MobileNet and Image Processing Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.h898-h906, June-2024, Available :http://www.jetir.org/papers/JETIR2406797.pdf

"Polycystic Ovary Syndrome detection using MobileNet and Image Processing Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pph898-h906, June-2024, Available at : http://www.jetir.org/papers/JETIR2406797.pdf