Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Vardhanabhuti, Varut | en_US |
dc.contributor.author | Kuo, Michael D. | en_US |
dc.date.accessioned | 2018-08-21T05:53:26Z | - |
dc.date.available | 2018-08-21T05:53:26Z | - |
dc.date.issued | 2018-01-01 | en_US |
dc.identifier.issn | 0883-5993 | en_US |
dc.identifier.uri | http://dx.doi.org/10.1097/RTI.0000000000000312 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/144695 | - |
dc.description.abstract | Radiogenomics provide a large-scale data analytical framework that aims to understand the broad multiscale relationships between the complex information encoded in medical images (including computational, quantitative, and semantic image features) and their underlying clinical, therapeutic, and biological associations. As such it is a powerful and increasingly important tool for both clinicians and researchers involved in the imaging, evaluation, understanding, and management of lung cancers. Herein we provide an overview of the growing field of lung cancer radiogenomics and its applications. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | lung cancer | en_US |
dc.subject | radiogenomics | en_US |
dc.subject | imaging | en_US |
dc.subject | genomics | en_US |
dc.title | Lung Cancer Radiogenomics: The Increasing Value of Imaging in Personalized Management of Lung Cancer Patients | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1097/RTI.0000000000000312 | en_US |
dc.identifier.journal | JOURNAL OF THORACIC IMAGING | en_US |
dc.citation.volume | 33 | en_US |
dc.citation.spage | 17 | en_US |
dc.citation.epage | 25 | en_US |
dc.contributor.department | 電機學院 | zh_TW |
dc.contributor.department | College of Electrical and Computer Engineering | en_US |
dc.identifier.wosnumber | WOS:000427640700003 | en_US |
Appears in Collections: | Articles |