Research into the potential benefits of artificial intelligence for comprehending the intricate
biology of cancer has grown as a result of the widespread use of deep learning and …

Artificial intelligence (AI) in oncology is advancing beyond algorithm development to
integration into clinical practice. This review describes the current state of the field, with a …

Brain tumors are often fatal. Therefore, accurate brain tumor image segmentation is critical
for the diagnosis, treatment, and monitoring of patients with these tumors. Magnetic …

Histopathology and genomic profiling are cornerstones of precision oncology and are
routinely obtained for patients with cancer. Traditionally, histopathology slides are manually …

The advent of digital pathology and the deployment of high‐throughput molecular
techniques are generating an unprecedented mass of data. Thanks to advances in …

Background Recent state-of-the-art sequencing technologies enable the investigation of
challenging regions in the human genome and expand the scope of variant benchmarking …

Introduction: Deep learning technology has been widely used in genetic research because
of its characteristics of computability, statistical analysis, and predictability. Herein, we aimed …

The detection of somatic DNA variants in tumor samples with low tumor purity or sequencing
depth remains a daunting challenge despite numerous attempts to address this problem. In …

Background: Although next generation sequencing (NGS) has been adopted as an essential
diagnostic tool in various diseases, NGS errors have been the most serious problem in …

Identifying somatic variants in tumor samples is a crucial task, which is often performed
using statistical methods and heuristic filters applied to short-read data. However, with the …