Radiomics with artificial intelligence: a practical guide for beginners.
Radiomics is a relatively new word for the field of radiology, meaning the extraction of a high number of quantitative features from medical images. Artificial intelligence (AI) is broadly a set of advanced computational algorithms that basically learn the patterns in the data provided to make predi...
| Publicado en: | Diagnostic & Interventional Radiology Vol. 25; no. 6; pp. 485 - 496 |
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| Autores principales: | , , , |
| Formato: | diagnostic images pictorial review tables/charts Journal Article |
| Publicado: |
Galenos Yayinevi Tic. LTD. STI
Nov/Dec2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=139613775&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 139613775 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13053825 39NM jtl: Diagnostic & Interventional Radiology issn: 13053825 maglogo: N pubinfo: dt: Nov/Dec2019 vid: 25 iid: 6 pid: 28155 pub: Galenos Yayinevi Tic. LTD. STI artinfo: ui: 139613775 139613775 NLM31650960 139613775 10.5152/dir.2019.19321 NLM31650960 139613775 ppf: 485 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Radiomics with artificial intelligence: a practical guide for beginners. aug: au: Koçak, Burak Durmaz, Emine Şebnem Ateş, Ece Kılıçkesmez, Özgür affil: Department of Radiology Büyükçekmece Mimar Sinan State Hospital, İstanbul, Turkey sug: subj: Specialties, Medical Methods Artificial Intelligence Forecasting Anxiety Algorithms Validation Studies Comparative Studies Evaluation Research Multicenter Studies ab: Radiomics is a relatively new word for the field of radiology, meaning the extraction of a high number of quantitative features from medical images. Artificial intelligence (AI) is broadly a set of advanced computational algorithms that basically learn the patterns in the data provided to make predictions on unseen data sets. Radiomics can be coupled with AI because of its better capability of handling a massive amount of data compared with the traditional statistical methods. Together, the primary purpose of these fields is to extract and analyze as much and meaningful hidden quantitative data as possible to be used in decision support. Nowadays, both radiomics and AI have been getting attention for their remarkable success in various radiological tasks, which has been met with anxiety by most of the radiologists due to the fear of replacement by intelligent machines. Considering ever-developing advances in computational power and availability of large data sets, the marriage of humans and machines in future clinical practice seems inevitable. Therefore, regardless of their feelings, the radiologists should be familiar with these concepts. Our goal in this paper was three-fold: first, to familiarize radiologists with the radiomics and AI; second, to encourage the radiologists to get involved in these ever-developing fields; and, third, to provide a set of recommendations for good practice in design and assessment of future works. pubtype: Academic Journal doctype: diagnostic images pictorial review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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