This study evaluates the quality of published research using artificial intelligence (AI) for
ovarian cancer diagnosis or prognosis using histopathology data. A systematic search of …

As data-driven science, artificial intelligence (AI) has paved a promising path toward an
evolving health system teeming with thrilling opportunities for precision oncology …

Histopathologic assessment is indispensable for diagnosing colorectal cancer (CRC).
However, manual evaluation of the diseased tissues under the microscope cannot reliably …

Histopathological image analysis is the gold standard to diagnose cancer. Carcinoma is a
subtype of cancer that constitutes more than 80% of all cancer cases. Squamous cell …

Histopathologic evaluation of biopsy slides is a critical step in diagnosing and subtyping
breast cancers. However, the connections between histology and multi-omics status have …

Purpose: Histopathology evaluation is the gold standard for diagnosing clear cell (ccRCC),
papillary, and chromophobe renal cell carcinoma (RCC). However, interrater variability has …

High-grade extrauterine serous carcinoma (HGSC) is an aggressive tumor with high rates of
recurrence, frequent chemotherapy resistance, and overall 5-year survival of less than 50 …

Ovarian cancer (OC) is a common reason for mortality among women. Deep learning has
recently proven better performance in predicting OC stages and subtypes. However, most of …

Background Long intergenic non-coding RNA 01094 (LINC01094) is probably a novel
regulator in cancer biology. This study aimed to probe into the function and mechanism of …

Ovarian cancer remains the most lethal gynecologic malignancy in the USA. For over twenty
years, epithelial-mesenchymal transition (EMT) has been characterized extensively in …