A review on the use of artificial intelligence for medical imaging of the lungs of patients with coronavirus disease 2019.
The results of research on the use of artificial intelligence (AI) for medical imaging of the lungs of patients with coronavirus disease 2019 (COVID-19) has been published in various forms. In this study, we reviewed the AI for diagnostic imaging of COVID-19 pneumonia. PubMed, arXiv, medRxiv, and Go...
| Publicado en: | Diagnostic & Interventional Radiology Vol. 26; no. 5; pp. 443 - 449 |
|---|---|
| Autores principales: | , , , , , |
| Formato: | diagnostic images research systematic review tables/charts Journal Article |
| Publicado: |
Galenos Yayinevi Tic. LTD. STI
Sep2020
|
| 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=145661577&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 145661577 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13053825 39NM jtl: Diagnostic & Interventional Radiology issn: 13053825 maglogo: N pubinfo: dt: Sep2020 vid: 26 iid: 5 pid: 28155 pub: Galenos Yayinevi Tic. LTD. STI artinfo: ui: 145661577 145661577 NLM32436845 145661577 10.5152/dir.2019.20294 NLM32436845 145661577 ppf: 443 ppct: 6 formats: fmt: @attributes: type: P tig: atl: A review on the use of artificial intelligence for medical imaging of the lungs of patients with coronavirus disease 2019. aug: au: Rintaro Ito Shingo Iwano Shinji Naganawa Ito, Rintaro Iwano, Shingo Naganawa, Shinji affil: Department of Innovative Biomedical Visualization sug: subj: Artificial Intelligence Pneumonia, Viral Image Interpretation, Computer Assisted Methods Radiography Methods COVID-19 Lung Tomography, X-Ray Computed Methods Sensitivity and Specificity Reproducibility of Results Disease Outbreaks Systematic Review ab: The results of research on the use of artificial intelligence (AI) for medical imaging of the lungs of patients with coronavirus disease 2019 (COVID-19) has been published in various forms. In this study, we reviewed the AI for diagnostic imaging of COVID-19 pneumonia. PubMed, arXiv, medRxiv, and Google scholar were used to search for AI studies. There were 15 studies of COVID-19 that used AI for medical imaging. Of these, 11 studies used AI for computed tomography (CT) and 4 used AI for chest radiography. Eight studies presented independent test data, 5 used disclosed data, and 4 disclosed the AI source codes. The number of datasets ranged from 106 to 5941, with sensitivities ranging from 0.67-1.00 and specificities ranging from 0.81-1.00 for prediction of COVID-19 pneumonia. Four studies with independent test datasets showed a breakdown of the data ratio and reported prediction of COVID-19 pneumonia with sensitivity, specificity, and area under the curve (AUC). These 4 studies showed very high sensitivity, specificity, and AUC, in the range of 0.9-0.98, 0.91-0.96, and 0.96-0.99, respectively. pubtype: Academic Journal doctype: diagnostic images research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|