BACKGROUND: Microvascular invasion (MVI) is essential for the management of hepatocellular carcinoma (HCC). However, MVI is hard to evaluate in patients without sufficient peri-tumoral tissue samples, which account for over a half of HCC patients.
PURPOSE: The use of predictive models in epidemiology is relatively narrow as most of the studies report results of traditional statistical models such as Linear, Logistic, or Cox regressions. In this study, a high-dimensional epidemiological cohort,...
Background and objectives: This study aimed to evaluate the association between warm ischemic time (WIT) and postoperative renal function using Trifecta achievement in patients with renal cell carcinoma (RCC) who underwent robotic (RAPN) or laparosco...
Data Sources Electronic search on PubMed, Cochrane, Scopus, Embase, Google Scholar, Saudi Digital Library and Web of Science, and hand searching carried out for studies published January 2000-March 2021. Language was restricted to English.Study selec...
Estimating age based on neuroimaging-derived data has become a popular approach to developing markers for brain integrity and health. While a variety of machine-learning algorithms can provide accurate predictions of age based on brain characteristic...
While the world continues to grapple with the devastating effects of the SARS-nCoV-2 virus, different scientific groups, including researchers from different parts of the world, are trying to collaborate to discover solutions to prevent the spread of...
BACKGROUND: Diabetic retinopathy is a leading cause of preventable blindness, especially in low-income and middle-income countries (LMICs). Deep-learning systems have the potential to enhance diabetic retinopathy screenings in these settings, yet pro...
Gleason grading, a risk stratification method for prostate cancer, is subjective and dependent on experience and expertise of the reporting pathologist. Deep Learning (DL) systems have shown promise in enhancing the objectivity and efficiency of Glea...
BACKGROUND: We collected information on patients with rectal adenocarcinoma in the United States from the Surveillance, Epidemiology, and EndResults (SEER) database. We used this information to establish a model that combined deep learning with a mul...
PURPOSE: Lunit INSIGHT CXR (Lunit) is a commercially available deep-learning algorithm-based decision support system for chest radiography (CXR). This retrospective study aimed to evaluate the concordance rate of radiologists and Lunit for thoracic a...