AIMC Topic: Colorectal Neoplasms

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European Society of Coloproctology Colorectal Robotic Surgery Training for the Trainers Course - the first pilot experience.

Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland
AIM: Currently, there is no established colorectal specific robotic surgery Train the Trainer (TTT) course. The aim was to develop and evaluate such a course which can then be further developed to be incorporated within the planned European Society o...

Explainable classifier for improving the accountability in decision-making for colorectal cancer diagnosis from histopathological images.

Journal of biomedical informatics
Pathologists are responsible for cancer type diagnoses from histopathological cancer tissues. However, it is known that microscopic examination is tedious and time-consuming. In recent years, a long list of machine learning approaches to image classi...

Deep learning to find colorectal polyps in colonoscopy: A systematic literature review.

Artificial intelligence in medicine
Colorectal cancer has a great incidence rate worldwide, but its early detection significantly increases the survival rate. Colonoscopy is the gold standard procedure for diagnosis and removal of colorectal lesions with potential to evolve into cancer...

Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning.

Gut
OBJECTIVE: Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), hi...

Clinical-Grade Detection of Microsatellite Instability in Colorectal Tumors by Deep Learning.

Gastroenterology
BACKGROUND & AIMS: Microsatellite instability (MSI) and mismatch-repair deficiency (dMMR) in colorectal tumors are used to select treatment for patients. Deep learning can detect MSI and dMMR in tumor samples on routine histology slides faster and le...

Utilizing artificial intelligence in endoscopy: a clinician's guide.

Expert review of gastroenterology & hepatology
INTRODUCTION: Artificial intelligence (AI) that surpasses human ability in image recognition is expected to be applied in the field of gastrointestinal endoscopes. Accordingly, its research and development (R &D) is being actively conducted. With the...

Diagnostic evaluation of a deep learning model for optical diagnosis of colorectal cancer.

Nature communications
Colonoscopy is commonly used to screen for colorectal cancer (CRC). We develop a deep learning model called CRCNet for optical diagnosis of CRC by training on 464,105 images from 12,179 patients and test its performance on 2263 patients from three in...

Challenges of Developing a Natural Language Processing Method With Electronic Health Records to Identify Persons With Chronic Mobility Disability.

Archives of physical medicine and rehabilitation
OBJECTIVE: To assess the utility of applying natural language processing (NLP) to electronic health records (EHRs) to identify individuals with chronic mobility disability.