Semantic segmentation and classification of polycystic ovarian disease using attention UNet, Pyspark, and ensemble learning model
Ashwini Kodipalli,
Susheela Devi,
Santosh Dasar
Abstract:Ovarian abnormality like polycystic ovarian disease (PCOD) is one of the most common diseases among women worldwide. PCOD not only has an impact on infertility but also hurts the psychological well‐being of women affecting their quality of life. In this study, a two‐class pattern learning problem is designed for the classification of PCOD. In total, 37 clinical parameters and abdominal ultrasound images of women are collected under the proper ethical protocol. Using only clinical data, an accuracy of 93.7% is … Show more
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