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 …

Objective Over the past years, the application of artificial intelligence (AI) in medicine has
increased rapidly, especially in diagnostics, and in the near future, the role of AI in medicine …

Ultrasound (US) imaging is the most commonly performed cross-sectional diagnostic
imaging modality in the practice of medicine. It is low-cost, non-ionizing, portable, and …

Exosomes are promising new biomarkers for colorectal cancer (CRC) diagnosis, due to their
rich biological fingerprints and high level of stability. However, the accurate detection of …

Background/Aim: This study aimed to use artificial intelligence (AI) to predict the pathological
diagnosis of ovarian tumors using patient information and data from preoperative …

Gynecological cancers including breast, cervical, ovarian, uterine, and vaginal, pose the
greatest threat to world health, with early identification being crucial to patient outcomes and …

Artificial intelligence (AI), also known as machine intelligence, is widely utilized in the
medical field, promoting medical advances. Malignant tumors are the critical focus of …

Simple Summary As a preliminary experiment to explore the possibility of clinical application
as a future reading assist, we present CNNs for the diagnosis of ovarian carcinomas and …

Artificial intelligence (AI) has gained prominence in medical imaging, particularly in
obstetrics and gynecology (OB/GYN), where ultrasound (US) is the preferred method. It is …

Simple Summary Gynecological malignancies are among the most common cancers with
significant morbidity and mortality worldwide. Management and overall patient survival is …