Latest AI and machine learning research in colon cancer for healthcare professionals.
Accurate prognosis is fundamental in planning an appropriate therapy for cancer patients. Consequent...
BACKGROUND AND AIMS: Clinical data suggest that the quality of optical diagnoses of colorectal polyp...
Standardized clinical pathways are useful tool to reduce variation in clinical management and may im...
The development of antitumor drugs has attracted cancer researchers and the identification of novel ...
To obtain a screening tool for colorectal cancer (CRC) based on gut microbiota, we seek here to iden...
BACKGROUND AND OBJECTIVE: infection is one of the most common chronic bacterial infections in the w...
Functional enrichment analysis is a fundamental and challenging task in bioinformatics. Most of the ...
PURPOSE: Convolutional neural networks have become rapidly popular for image recognition and image a...
Lung cancer is the leading cause of cancer death around the world, and lung cancer screening remains...
Polyps in the colon can potentially become malignant cancer tissues where early detection and remova...
BACKGROUND AND AIMS: The prognosis of esophageal cancer is relatively poor. Patients are usually dia...
BACKGROUND: Computer-aided diagnosis (CAD) for colonoscopy may help endoscopists distinguish neoplas...
OBJECTIVE:: Genetic phenotype plays a central role in making treatment decisions of lung adenocarcin...
BACKGROUND: The early diagnosis of colorectal cancer (CRC) is associated with improved survival rate...
In this paper, we propose a method for automatically annotating slide images from colorectal tissue ...
BACKGROUND & AIMS: The benefit of colonoscopy for colorectal cancer prevention depends on the adenom...
Colorectal cancer is the fourth leading cause of cancer deaths worldwide and the second leading caus...
Laparoscopic complete mesocolic excision (CME) for transverse colon cancer is technically challengi...
Implications of plasminogen activator inhibitor-1 (PAI-1) in colonic polyps remain elusive. A prospe...
To realize the full potential of deep learning for medical imaging, large annotated datasets are req...
Constructive (generative) machine learning enables the automated generation of novel chemical struct...