Published April 2021
| Version v1
Journal article
Texture feature-based machine learning classifier could assist in the diagnosis of COVID-19
- 1. Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing (China)
- 2. Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing (China)
- 3. Beijing Youan Hospital, Capital Medical University, Beijing (China)
Description
Highlights: • COVID-19 patients show similar clinical manifestations as other pneumonias. • Specific pattern of CT texture features attributes to COVID-19. • Texture feature overrides clinical sign given the recognition of COVID-19. • Radiomics-based machine learning assists in the diagnosis of COVID-19. Differentiating COVID-19 from other acute infectious pneumonias rapidly is challenging at present. This study aims to improve the diagnosis of COVID-19 using computed tomography (CT).
Availability note (English)
Available from http://dx.doi.org/10.1016/j.ejrad.2021.109602Additional details
Identifiers
- DOI
- 10.1016/j.ejrad.2021.109602;
- PII
- S0720048X21000826;
Publishing Information
- Journal Title
- European Journal of Radiology
- Journal Volume
- 137
- Journal Page Range
- vp.
- ISSN
- 0720-048X
- CODEN
- EJRADR
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 53110522
- Subject category
- S62: RADIOLOGY AND NUCLEAR MEDICINE;
- Descriptors DEI
- COMPUTERIZED TOMOGRAPHY; CORONAVIRUSES; DIAGNOSIS; MACHINE LEARNING; PATIENTS; PNEUMONIA; POLYMERASE CHAIN REACTION; RADIOMICS
- Descriptors DEC
- ALGORITHMS; ARTIFICIAL INTELLIGENCE; DIAGNOSTIC TECHNIQUES; DISEASES; GENE AMPLIFICATION; INFECTIOUS DISEASES; LEARNING; MATHEMATICAL LOGIC; MEDICINE; MICROORGANISMS; NUCLEAR MEDICINE; PARASITES; RADIOLOGY; RESPIRATORY SYSTEM DISEASES; TOMOGRAPHY; VIRAL DISEASES; VIRUSES; ZOONOTIC DISEASES
Optional Information
- Copyright
- Copyright (c) 2021 Elsevier B.V. All rights reserved.