Cancer is a major medical problem worldwide. Due to its high heterogeneity, the use of the
same drugs or surgical methods in patients with the same tumor may have different curative …

Background Artificial intelligence (AI) is increasingly being used in medical imaging
analysis. We aimed to evaluate the diagnostic accuracy of AI models used for detection of …

Background Machine learning (ML) has been introduced in various fields of healthcare. In
colorectal surgery, the role of ML has yet to be reported. In this systematic review, an …

Background Machine learning (ML) has been successful in several fields of healthcare,
however the use of ML within bariatric surgery seems to be limited. In this systematic review …

The considerable burden of colorectal cancer and the rising trend in young adults
emphasize the necessity of understanding its underlying mechanisms, providing new …

Simple Summary Cancer remains one of the leading causes of death worldwide, which
emphasizes the need for its early and accurate diagnosis and prognosis. Our review …

The main therapeutic options for colorectal cancer are surgical resection and adjuvant
chemotherapy in non-metastatic disease. However, the evaluation of the overall adjuvant …

Gastric cancer (GC), with a 5-year survival rate of less than 40%, is known as the fourth
principal reason of cancer-related mortality over the world. This study aims to develop …

Abstract Machine learning is an established data interpretation tool for the development of
processing, extracting and extrapolating evocative results from complex data sets. Data …

Computed tomography (CT) introduced medicine to digital imaging. This occurred in the
early 1970s and it was the start of the digital medical imaging revolution. The resulting …