Results 91 to 100 of about 809,703 (372)
Colorectal Neuroendocrine Neoplasms: Areas of Unmet Need [PDF]
Neuroendocrinology, 2018 The subject of colorectal neuroendocrine neoplasms (NENs), subdivided into well-differentiated NENs, termed neuroendocrine tumours (NETs; grade (G) 1 and 2), and poorly differentiated NENs, termed neuroendocrine carcinomas (NECs; G3) according to the 2010 World Health Organisation (WHO) classification, has arguably not had as much attention or study as
Ramage, JK +9 more
openaire +3 more sources
Molecular Oncology, EarlyView.Consensus molecular subtypes (CMS1‐4) have been identified to study colorectal cancer heterogeneity and serve as potential biomarkers. In this study, we developed and evaluated NanoCMSer, a NanoString‐based classifier using 55 genes, optimized for FF and FFPE to facilitate the clinical evaluation of CMS subtyping.
Arezo Torang +10 more
wiley +1 more source
Large Colorectal Lesions: Evaluation and Management
GE: Portuguese Journal of Gastroenterology, 2016 In the last years, a distinctive interest has been raised on large polypoid and non-polypoid colorectal tumors, and specially on flat neoplastic lesions ≥20 mm tending to grow laterally, the so called laterally spreading tumors (LST).
Carlos Eduardo Oliveira dos Santos +2 more
doaj +1 more source
Molecular Oncology, EarlyView.Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran +16 more
wiley +1 more source
Deep Transfer Learning for Texture Classification in Colorectal Cancer Histology [PDF]
arXiv, 2020 Microscopic examination of tissues or histopathology is one of the diagnostic procedures for detecting colorectal cancer. The pathologist involved in such an examination usually identifies tissue type based on texture analysis, especially focusing on tumour-stroma ratio.
arxiv
Automatic Polyp Segmentation using Fully Convolutional Neural Network [PDF]
arXiv, 2021 Colorectal cancer is one of fatal cancer worldwide. Colonoscopy is the standard treatment for examination, localization, and removal of colorectal polyps. However, it has been shown that the miss-rate of colorectal polyps during colonoscopy is between 6 to 27%.
arxiv
Endoscopic submucosal dissection for large colorectal neoplasms
Digestive Endoscopy, 2017 Endoscopic submucosal dissection (ESD) for colorectal neoplasms (CRN) of >50 mm is considered technically difficult. The ITknife nano™ was developed specifically for ESD of CRN and esophageal superficial neoplasms; however, only limited data are ...
K. Imai +4 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.The authors conducted a retrospective study of 94 patients with advanced cancer who underwent next‐generation sequencing (NGS) gene panel analysis and received targeted treatments when applicable. Results further support evidence indicating that molecular profiling provides clinical benefit.
Michaël Dang +3 more
wiley +1 more source
Deep-Learning for Classification of Colorectal Polyps on Whole-Slide Images [PDF]
arXiv, 2017 Histopathological characterization of colorectal polyps is an important principle for determining the risk of colorectal cancer and future rates of surveillance for patients. This characterization is time-intensive, requires years of specialized training, and suffers from significant inter-observer and intra-observer variability. In this work, we built
arxiv
Canadian Journal of Gastroenterology, 2013 BACKGROUND AND OBJECTIVES: The diagnostic value of stool DNA (sDNA) testing for colorectal neoplasms remains controversial. To compensate for the lack of large-scale unbiased population studies, a meta-analysis was performed to evaluate the diagnostic ...
Hua Yang +9 more
doaj +1 more source