Latest AI and machine learning research in colon cancer for healthcare professionals.
<b>Indroduction:</b> Colonoscopy is an acclaimed screening test to detect colorectal can...
Colorectal polyps are generally benign alterations that, if not identified promptly and managed su...
A distinct feature of pancreatic ductal adenocarcinoma (PDAC) is a prominent tumor microenvironmen...
Gene expression profiling of new or modified cell lines becomes routine today; however, obtaining co...
Lung adenocarcinoma (LUAD) is a tumour characterized by high tumour heterogeneity. Although there ar...
The progression of lung adenocarcinoma (LUAD) from atypical adenomatous hyperplasia (AAH) to invasiv...
Lung adenocarcinoma (LUAD) is a leading cause of cancer-related deaths, and improving prognostic acc...
Providing robust prognosis predictions for cancers with limited data samples remains a challenge for...
Accurate classification between tumor MicroSatellite Stability (MSS) and Instability (MSI) is crucia...
Federated Learning (FL) is emerging in the medical field to address the need for diverse datasets wh...
This work introduces EffiSegNet, a novel segmentation framework leveraging transfer learning with a ...
Despite the widespread development of ontologies in many domains of healthcare, the field of colorec...
Graph-based learning approaches, due to their ability to encode tissue/organ structure information, ...
In recent years, long non-coding RNAs (lncRNAs) have emerged as potential regulators of biological p...
Prediction of genetic biomarkers, e.g., microsatellite instability and BRAF in colorectal cancer i...
Colorectal cancer is the most common malignant tumor of digestive tract, and the incidence of colore...
BACKGROUND: Colorectal cancer significantly impacts global health, with unplanned reoperations post-...
The investigation into individual survival rates within the patient population was typically conduct...
UNLABELLED: Deep learning may detect biologically important signals embedded in tumor morphologic fe...
Recent studies have extensively used deep learning algorithms to analyze gene expression to predict ...
Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans ...