About: Artificial neural networks distinguish among subtypes of neoplastic colorectal lesions

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scientific article published on 01 March 2002

Attributes	Values
rdf:type	Item
description	wetenschappelijk artikel (nl) наукова стаття, опублікована в березні 2002 (uk) article scientifique publié en 2002 (fr) im März 2002 veröffentlichter wissenschaftlicher Artikel (de) artículu científicu espublizáu en marzu de 2002 (ast) scientific article published on 01 March 2002 (en)
publication date	wds:Q77718385-D0496B7C-BABE-4503-821B-479ECBEDE565
publication date	2002-03-01 00:00:00Z (xsd:dateTime)
language of work or name	wds:Q77718385-EA9E0AD6-1655-43D8-8982-300F673D7B8F
language of work or name	English
cites work	wds:Q77718385-A1DD4B53-F117-4AEF-9ABF-8E690F96EC63
cites work	Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling
author name string	wds:Q77718385-155DCDB7-CED1-4C54-BCAB-77D56D4829E4 wds:Q77718385-16B37106-B4DE-4603-A108-D4F0805B601C wds:Q77718385-1BB15DCB-0A5D-4FB6-8FCD-54A24E1A2EDD wds:Q77718385-210B68FC-5A37-488B-B2B3-2BF441411839 wds:Q77718385-559EC29A-D46E-4A09-894D-C010B3F057EB wds:Q77718385-5E337340-D4B2-4BFB-B9AB-38004064AEF7 wds:Q77718385-64B29149-5CD4-475E-A55E-444C8ED69A95 wds:Q77718385-7BDD7A9F-9ABC-4DE6-8AB6-6E6410674C9E wds:Q77718385-87FC1CB3-C09F-4A0C-9B5D-FB898AC3C57E wds:Q77718385-8B2B6EB5-41B0-497D-B3E9-968113C91438 wds:Q77718385-9E3152F5-B494-451D-A231-CD56516E5ECF wds:Q77718385-9F97C4FF-8DB8-46BF-8216-62154392A58C wds:Q77718385-A2C5EC7D-85B9-457E-9762-8E4AAA1602F7 wds:Q77718385-CC9328D7-4F4B-4EF5-98B7-F152149F3020 wds:Q77718385-E4954B24-7D5A-4374-BA1B-8ACFB0BA03E8 wds:Q77718385-E865370D-D8E3-4030-8014-A291BB9D0DB4 wds:Q77718385-F096465A-13DE-4356-9129-9B4683D4BA73
author name string	Yan Xu David Shibata Stephen J Meltzer Fumiaki Sato Jing Yin Florin M Selaru Tong Zou Suna Wang Prodromos Hytiroglou Noam Harpaz John M Abraham Yuriko Mori Andreea Olaru Anatoly Leytin Thomas C Liu Charlie Twigg Valentina Shustova
rdfs:label	Artificial neural networks distinguish among subtypes of neoplastic colorectal lesions (en) Artificial neural networks distinguish among subtypes of neoplastic colorectal lesions (nl)
skos:prefLabel	Artificial neural networks distinguish among subtypes of neoplastic colorectal lesions (en) Artificial neural networks distinguish among subtypes of neoplastic colorectal lesions (nl)
name	Artificial neural networks distinguish among subtypes of neoplastic colorectal lesions (en) Artificial neural networks distinguish among subtypes of neoplastic colorectal lesions (nl)
title	wds:Q77718385-4B289B6D-2A40-4E3A-B7FA-A1EBA77D14B8
title	Artificial neural networks distinguish among subtypes of neoplastic colorectal lesions (en)
page(s)	wds:Q77718385-F0007CE0-81B6-4A06-B698-6EF3CD9460B8
page(s)	606-613
instance of	wds:Q77718385-47408528-77F6-4618-BEE1-E9C56E96559B
instance of	scholarly article
main subject	wds:Q77718385-5F61E4AA-5D90-491A-9A6F-356BEE028A91
main subject	artificial neural network
PubMed ID	wds:Q77718385-2A9D8EC5-A382-4BF6-B93A-2C08995F3A4B
PubMed ID	http://rdf.ncbi.nlm.nih.gov/pubchem/reference/11874992
PubMed ID	11874992
published in	wds:Q77718385-63446B6C-3788-442A-8B60-3B9A5621C122
published in	Gastroenterology
issue	wds:Q77718385-2EB9F321-C592-406D-A224-42C36FC99108
volume	wds:Q77718385-3E95048E-D792-434A-9EDF-33A7F1CCC0AC
issue	3
volume	122
DOI	wds:Q77718385-BE061C27-C191-4B3C-B9AF-B9A8E564C863
DOI	http://dx.doi.org/10.1053/GAST.2002.31904
DOI	10.1053/GAST.2002.31904
is about of	https://www.wikidata.org/wiki/Special:EntityData/Q77718385
is cites work of	Dynamic changes in the expression of MicroRNA-31 during inflammatory bowel disease-associated neoplastic transformation Cancer in inflammatory bowel disease Trends in microarray analysis Gene expression array profile of human osteosarcoma Strategies for detecting colon cancer and/or dysplasia in patients with inflammatory bowel disease Long-term follow-up after polypectomy treatment for adenoma-like dysplastic lesions in ulcerative colitis Prediction of outcome in acute lower-gastrointestinal haemorrhage based on an artificial neural network: internal and external validation of a predictive model Looking beyond morphology: cancer gene expression profiling using DNA microarrays Rules of evidence for cancer molecular-marker discovery and validation Prediction of survival in patients with esophageal carcinoma using artificial neural networks Translational biomedical informatics in the cloud: present and future Difference of gene expression profiles between esophageal carcinoma and its pericancerous epithelium by gene chip A multigene expression panel for the molecular diagnosis of Barrett's esophagus and Barrett's adenocarcinoma of the esophagus. Artificial neural networks for diagnosis and survival prediction in colon cancer Application of cDNA microarrays to generate a molecular taxonomy capable of distinguishing between colon cancer and normal colon Artificial neural networks in the recognition of the presence of thyroid disease in patients with atrophic body gastritis Whole-Exome Sequencing Analyses of Inflammatory Bowel Disease-Associated Colorectal Cancers Clinical significance of type V(I) pit pattern subclassification in determining the depth of invasion of colorectal neoplasms Analysis of differential gene expression in colorectal cancer and stroma using fluorescence-activated cell sorting purification Classification tool for the systematic histological assessment of hepatocellular carcinoma, macroregenerative nodules, and dysplastic nodules in cirrhotic liver Gene expression data classification using consensus independent component analysis Beyond Field Effect: Analysis of Shrunken Centroids in Normal Esophageal Epithelia Detects Concomitant Esophageal Adenocarcinoma Added value of a resting ECG neural network that predicts cardiovascular mortality. The use of artificial neural networks in prediction of congenital CMV outcome from sequence data. Architectures and accuracy of artificial neural network for disease classification from omics data Predicting outcomes in patients with perforated gastroduodenal ulcers: artificial neural network modelling indicates a highly complex disease

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