In order to ensure that ovarian cancer patients access appropriate treatment to improve the
outcome of this disease, accurate characterization before any surgery on ovarian pathology …

The explosive growth of data in volume, velocity and diversity that are produced by medical
applications has contributed to abundance of big data. Current solutions for efficient data …

OBJECTIVE: To perform a systematic review of the literature on the accuracy of prediction
models in the preoperative assessment of adnexal masses. DATA SOURCES: Studies were …

Chronic pain has been traditionally defined by pain duration, but this approach has limited
empirical support and does not account for chronic pain's multi-dimensionality. This study …

Purpose: To retrospectively evaluate the diagnostic performance of dynamic contrast
material–enhanced magnetic resonance (MR) imaging for the characterization of ovarian …

Purpose To evaluate the utility of dynamic contrast enhancement (DCE) MRI for
distinguishing among benign, borderline and invasive epithelial ovarian tumors. Materials …

OBJECTIVE: To systematically review the existing literature in order to determine the optimal
strategy for preoperative identification of the adnexal mass suspicious for ovarian cancer …

The aim of this paper was to explore the role of artificial intelligence (AI) applied to
ultrasound imaging in gynecology oncology. Web of Science, PubMed, and Scopus …

Purpose: To externally validate and compare the performance of previously published
diagnostic models developed to predict malignancy in adnexal masses. Experimental …

Purpose: To prospectively test the mathematical models for calculation of the risk of
malignancy in adnexal masses that were developed on the International Ovarian Tumor …