Endometrial cancer (EC) is a prevalent uterine cancer that remains a major contributor to
cancer-associated morbidity and mortality. EC diagnosed at advanced stages shows a poor …

Introduction Gynecological cancers pose a significant threat to women worldwide, especially
those in resource-limited settings. Human analysis of images remains the primary method of …

Purpose Identifying optimal machine learning pipelines for computer-aided diagnosis is key
for the development of robust, reproducible, and clinically relevant imaging biomarkers for …

Gynaecological cancers encompass a spectrum of malignancies affecting the female
reproductive system, comprising the cervix, uterus, ovaries, vulva, vagina, and fallopian …

Rising endometrial cancer (EC) incidence and disease mortality represent a serious
concern for women, particularly in countries with rapid socioeconomic transitions where the …

Endometrial cancer screening is crucial for clinical treatment. Currently, cytopathologists
analyze cytopathology images is considered a popular screening method, but manual …

Objective To assess the methodological quality of radiomics-based models in endometrial
cancer using the radiomics quality score (RQS) and METhodological radiomICs score …

Endometrial cancer, the fourth most common cancer in females in the United States, with the
lifetime risk for developing this disease is approximately 2.8% in women. Precise histologic …

Artificial intelligence has yielded remarkably promising results in several medical fields,
namely those with a strong imaging component. Gynecology relies heavily on imaging since …

Endometrial cancer, one of the three major malignant tumors of the female genitalia, has
seen an increase in incidence in recent years. The 5-year survival rate for early endometrial …