About: CT-based radiomics signature for differentiating solitary granulomatous nodules from solid lung adenocarcinoma

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: CT-based radiomics signature for differentiating solitary granulomatous nodules from solid lung adenocarcinoma Goto Sponge NotDistinct Permalink

An Entity of Type : wikibase:Item, within Data Space : wikidata.demo.openlinksw.com associated with source document(s)

scientific article published on 17 September 2018

Attributes	Values
rdf:type	Item
description	wetenschappelijk artikel (nl) наукова стаття, опублікована у вересні 2018 (uk) artículu científicu espublizáu en setiembre de 2018 (ast) scientific article published on 17 September 2018 (en)
publication date	wds:Q93077814-6B696C9F-24F9-432A-BB45-AB6B70F89E03
publication date	2018-09-17 00:00:00Z (xsd:dateTime)
author name string	wds:Q93077814-0EE51C6A-9FB5-4B78-B6FE-7F5598A908CF wds:Q93077814-1022DD77-A78B-49A9-A9DC-A9E38239DA28 wds:Q93077814-5175840A-6C33-47DB-9BDE-A830D80B6265 wds:Q93077814-69768FBE-BDA5-4E79-A7DA-D86FB9C88275 wds:Q93077814-A10E82D4-4809-4556-A676-E66488E5F214 wds:Q93077814-EEDE4E18-ACBD-48A8-B9EC-CC7170EAE33C wds:Q93077814-F1EF98A9-2181-4920-B2A3-FB3A3484C219
author name string	Weiwei Li Jiao Wang Jianxing He Yubao Guan Chunbo Liu Dashan Gao Xinguan Yang
rdfs:label	CT-based radiomics signature for differentiating solitary granulomatous nodules from solid lung adenocarcinoma (en) CT-based radiomics signature for differentiating solitary granulomatous nodules from solid lung adenocarcinoma (nl)
skos:prefLabel	CT-based radiomics signature for differentiating solitary granulomatous nodules from solid lung adenocarcinoma (en) CT-based radiomics signature for differentiating solitary granulomatous nodules from solid lung adenocarcinoma (nl)
name	CT-based radiomics signature for differentiating solitary granulomatous nodules from solid lung adenocarcinoma (en) CT-based radiomics signature for differentiating solitary granulomatous nodules from solid lung adenocarcinoma (nl)
title	wds:Q93077814-10230F2E-021C-4EA9-8790-AA0381E0C314
title	CT-based radiomics signature for differentiating solitary granulomatous nodules from solid lung adenocarcinoma (en)
page(s)	wds:Q93077814-6D20B697-3C02-4923-B87A-D564DF224001
page(s)	109-114
instance of	wds:Q93077814-FB332CAD-5943-4DD8-9421-EC02F00A7F6C
instance of	scholarly article
main subject	wds:Q93077814-74640F0F-12E1-4115-B301-3C3D97BC6FAC
main subject	adenocarcinoma
PubMed ID	wds:Q93077814-F514B33B-8059-4497-B55C-DBF60AF1F3A5
PubMed ID	http://rdf.ncbi.nlm.nih.gov/pubchem/reference/30429007
PubMed ID	30429007
published in	wds:Q93077814-A0C89EB5-36CD-4EB9-8868-EAEA4E0FEF24
published in	Lung Cancer
volume	wds:Q93077814-46FF8D6C-E5B3-49BD-B118-8A54BBA2B7B7
volume	125
DOI	wds:Q93077814-F56B7C5D-2BE3-47ED-9E62-C440489F6FE4
DOI	http://dx.doi.org/10.1016/J.LUNGCAN.2018.09.013
DOI	10.1016/J.LUNGCAN.2018.09.013
is about of	https://www.wikidata.org/wiki/Special:EntityData/Q93077814
is cites work of	A CT-based radiomics nomogram for prediction of lung adenocarcinomas and granulomatous lesions in patient with solitary sub-centimeter solid nodules Computed Tomography-Based Radiomics Signature: A Potential Indicator of Epidermal Growth Factor Receptor Mutation in Pulmonary Adenocarcinoma Appearing as a Subsolid Nodule Clinical, Conventional CT and Radiomic Feature-Based Machine Learning Models for Predicting ALK Rearrangement Status in Lung Adenocarcinoma Patients Predicting Lung Cancer Risk of Incidental Solid and Subsolid Pulmonary Nodules in Different Sizes
is cites work of	wds:Q97528044-921788E0-5CF7-4E5B-A038-7472E6FB8DFC wds:Q92766649-F450F195-BB75-4CF8-9B19-9BF14F0F0374 wds:Q91713532-7D66A2A9-DA07-48E6-872F-D11A7D1F044A wds:Q99565267-7A5FBA7D-9ED5-4D12-BB82-A4D35E72D502

Faceted Search & Find service v1.16.117 as of May 05 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3239 as of May 5 2024, on Linux (x86_64-centos_6-linux-gnu), Single-Server Edition (378 GB total memory, 172 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software