Objectives To establish a deep learning (DL) model for predicting tumor grades and
expression of pathologic markers of meningioma. Methods A total of 1192 meningioma …

Abstract The adaptation of Artificial Intelligence can radically reshape the entire healthcare
industry. This paper proposes a comparative analysis of four Machine Learning algorithms …

Purpose: Gastric cancer remains the leading cause of cancer-related deaths in Northeast
Asia. Population-based endoscopic screenings in the region have yielded successful results …

Purpose There are millions of people who lose their life due to several types of fatal
diseases. Cancer is one of the most fatal diseases which may be due to obesity, alcohol …

Computational pathology (CPath) algorithms detect, segment or classify cancer in whole
slide images, approaching or even exceeding the accuracy of pathologists. Challenges …

Objectives This study aimed to develop and validate a combined nomogram model based
on deep learning (DL) contrast-enhanced ultrasound (CEUS) and clinical factors to …

Unmasking the decision making process of machine learning models is essential for
implementing diagnostic support systems in clinical practice. Here, we demonstrate that …

Background There is increasing interest in the use of artificial intelligence (AI) in pathology
to increase accuracy and efficiency. To date, studies of clinicians' perceptions of AI have …

About 40% of lung cancers are lung adenocarcinoma (LUAD), the most prevalent type of
cancer and the one with the highest mortality rate. Although Lung cancers are generally …

Histological analysis of hepatic tissue specimens is essential for evaluating the pathology of
several liver disorders such as chronic liver diseases, hepatocellular carcinomas, liver …