Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral
part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer …

As in other domains, artificial intelligence is becoming increasingly important in medicine. In
particular, deep learning-based pattern recognition methods can advance the field of …

Gastric Cancer is the most common malignancy of the digestive tract, which is the third
leading cause of cancer-related mortality worldwide. The early prognosis methods …

Recent advances in artificial intelligence show tremendous promise to improve the
accuracy, reproducibility, and availability of medical diagnostics across a number of medical …

Colorectal cancer (CRC) is one of the most common cancers requiring early pathologic
diagnosis using colonoscopy biopsy samples. Recently, artificial intelligence (AI) has made …

We report the ability of two deep learning-based decision systems to stratify non-small cell
lung cancer (NSCLC) patients treated with checkpoint inhibitor therapy into two distinct …

Colorectal imaging improves on diagnosis of colorectal diseases by providing colorectal
images. Manual diagnosis of colorectal disease is labor‐intensive and time‐consuming. In …

Background: Digital pathology, in its primary meaning, describes the utilization of computer
screens to view scanned histology slides. Digitized tissue sections can be easily shared for …

Colorectal cancer (CRC) is one of the most common cancers among humans, its diagnosis
is made through the visual analysis of tissue samples by pathologists; artificial intelligence …

Many existing intelligent recognition technologies require huge datasets for model learning.
However, it is not easy to collect rectal cancer images, so the performance is usually low …