"MODERN METHODOLOGIES OF SCORING SYSTEMS FOR ULTRASOUND DIAGNOSIS OF OVARIAN CANCER: DIFFERENTIATION AND PROGNOSIS"

Abstract

Ovarian cancer remains a significant public health concern, owing to its high mortality rate and propensity for recurrence. Although improvements in screening and diagnostic methods have been made, the disease frequently goes undetected until advanced stages, where the prognosis is unfavorable. This study aims to improve the differentiation of ovarian masses through ultrasound imaging and advanced assessment techniques. The study analyzed data from 121 patients with histologically confirmed ovarian tumors, using both transvaginal and transabdominal ultrasound techniques. Logistic regression models and machine learning algorithms were utilized to analyze the multidimensional ultrasound data with the aim of enhancing the accuracy of differentiating between benign and malignant tumors.