Background Accurate identification of ovarian cancer (OC) is of paramount importance in
clinical treatment success. Artificial intelligence (AI) is a potentially reliable assistant for the …

The SARS-CoV-2 virus has caused a pandemic, infecting nearly 80 million people
worldwide, with mortality exceeding six million. The average survival span is just 14 days …

Background Upon the discovery of ovarian cysts, obstetricians, gynecologists, and
ultrasound examiners must address the common clinical challenge of distinguishing …

Background The preoperative diagnosis of peritoneal metastasis (PM) in epithelial ovarian
cancer (EOC) is challenging and can impact clinical decision‐making. Purpose To …

Ovarian cancer, characterized by uncontrolled cell growth in the ovaries, poses a significant
threat to women's reproductive health. Often referred to as the “silent killer,” it is notorious for …

Ovarian cancer poses a major worldwide health issue, marked by high death rates and a
deficiency in reliable diagnostic methods. The precise and prompt detection of ovarian …

Artificial intelligence (AI) has emerged as a crucial technique for extracting high‑throughput
information from various sources, including medical images, pathological images, and …

Background Ovarian cancer (OC) is a severe gynecological malignancy with significant
diagnostic and therapeutic challenges. The discovery of reliable cancer biomarkers can be …

Ovarian cancer is a significant health concern because of its high mortality rates and
potential to cause glomerular injury, which can obstruct the urinary tract. It is very crucial to …

Background and objectives: By extracting this information, Machine or Deep Learning
(ML/DL)-based autonomous data analysis tools can assist clinicians and cancer researchers …