BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

504 related articles for article (PubMed ID: 34052882)

  • 1. COVID-19 classification of X-ray images using deep neural networks.
    Keidar D; Yaron D; Goldstein E; Shachar Y; Blass A; Charbinsky L; Aharony I; Lifshitz L; Lumelsky D; Neeman Z; Mizrachi M; Hajouj M; Eizenbach N; Sela E; Weiss CS; Levin P; Benjaminov O; Bachar GN; Tamir S; Rapson Y; Suhami D; Atar E; Dror AA; Bogot NR; Grubstein A; Shabshin N; Elyada YM; Eldar YC
    Eur Radiol; 2021 Dec; 31(12):9654-9663. PubMed ID: 34052882
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy.
    Castiglioni I; Ippolito D; Interlenghi M; Monti CB; Salvatore C; Schiaffino S; Polidori A; Gandola D; Messa C; Sardanelli F
    Eur Radiol Exp; 2021 Feb; 5(1):7. PubMed ID: 33527198
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Computer-aided COVID-19 diagnosis and a comparison of deep learners using augmented CXRs.
    Naseer A; Tamoor M; Azhar A
    J Xray Sci Technol; 2022; 30(1):89-109. PubMed ID: 34842222
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Application of deep learning to identify COVID-19 infection in posteroanterior chest X-rays.
    Maharjan J; Calvert J; Pellegrini E; Green-Saxena A; Hoffman J; McCoy A; Mao Q; Das R
    Clin Imaging; 2021 Dec; 80():268-273. PubMed ID: 34425544
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Deep Learning for Reliable Classification of COVID-19, MERS, and SARS from Chest X-ray Images.
    Tahir AM; Qiblawey Y; Khandakar A; Rahman T; Khurshid U; Musharavati F; Islam MT; Kiranyaz S; Al-Maadeed S; Chowdhury MEH
    Cognit Comput; 2022; 14(5):1752-1772. PubMed ID: 35035591
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Optimized chest X-ray image semantic segmentation networks for COVID-19 early detection.
    Gopatoti A; Vijayalakshmi P
    J Xray Sci Technol; 2022; 30(3):491-512. PubMed ID: 35213339
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Multi-View Ensemble Convolutional Neural Network to Improve Classification of Pneumonia in Low Contrast Chest X-Ray Images.
    Ferreira JR; Armando Cardona Cardenas D; Moreno RA; de Fatima de Sa Rebelo M; Krieger JE; Antonio Gutierrez M
    Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1238-1241. PubMed ID: 33018211
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images.
    Rahman T; Khandakar A; Qiblawey Y; Tahir A; Kiranyaz S; Abul Kashem SB; Islam MT; Al Maadeed S; Zughaier SM; Khan MS; Chowdhury MEH
    Comput Biol Med; 2021 May; 132():104319. PubMed ID: 33799220
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Hybrid ensemble model for differential diagnosis between COVID-19 and common viral pneumonia by chest X-ray radiograph.
    Jin W; Dong S; Dong C; Ye X
    Comput Biol Med; 2021 Apr; 131():104252. PubMed ID: 33610001
    [TBL] [Abstract][Full Text] [Related]  

  • 10. COVID-DSNet: A novel deep convolutional neural network for detection of coronavirus (SARS-CoV-2) cases from CT and Chest X-Ray images.
    Reis HC; Turk V
    Artif Intell Med; 2022 Dec; 134():102427. PubMed ID: 36462906
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Deep Learning Algorithm for COVID-19 Classification Using Chest X-Ray Images.
    V J S; D JF
    Comput Math Methods Med; 2021; 2021():9269173. PubMed ID: 34795794
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Explainable COVID-19 Detection Based on Chest X-rays Using an End-to-End RegNet Architecture.
    Chetoui M; Akhloufi MA; Bouattane EM; Abdulnour J; Roux S; Bernard CD
    Viruses; 2023 Jun; 15(6):. PubMed ID: 37376626
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Fast and Accurate Detection of COVID-19 Along With 14 Other Chest Pathologies Using a Multi-Level Classification: Algorithm Development and Validation Study.
    Albahli S; Yar GNAH
    J Med Internet Res; 2021 Feb; 23(2):e23693. PubMed ID: 33529154
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A Deep Learning Model for Diagnosing COVID-19 and Pneumonia through X-ray.
    Liu X; Wu W; Chun-Wei Lin J; Liu S
    Curr Med Imaging; 2023; 19(4):333-346. PubMed ID: 35692156
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Thorax computed tomography (CTX) guided ground truth annotation of CHEST radiographs (CXR) for improved classification and detection of COVID-19.
    Ertürk ŞM; Toprak T; Cömert RG; Candemir C; Cingöz E; Akyol Sari ZN; Ercan CC; Düvek E; Ersoy B; Karapinar E; Tunaci A; Selver MA
    Int J Numer Method Biomed Eng; 2024 Jun; 40(6):e3823. PubMed ID: 38587026
    [TBL] [Abstract][Full Text] [Related]  

  • 16. An Efficient Deep Learning Model to Detect COVID-19 Using Chest X-ray Images.
    Chakraborty S; Murali B; Mitra AK
    Int J Environ Res Public Health; 2022 Feb; 19(4):. PubMed ID: 35206201
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Inverted bell-curve-based ensemble of deep learning models for detection of COVID-19 from chest X-rays.
    Paul A; Basu A; Mahmud M; Kaiser MS; Sarkar R
    Neural Comput Appl; 2022 Jan; ():1-15. PubMed ID: 35013650
    [TBL] [Abstract][Full Text] [Related]  

  • 18. COVID-19 detection in CT and CXR images using deep learning models.
    Chouat I; Echtioui A; Khemakhem R; Zouch W; Ghorbel M; Hamida AB
    Biogerontology; 2022 Feb; 23(1):65-84. PubMed ID: 35064446
    [TBL] [Abstract][Full Text] [Related]  

  • 19. DDA-SSNets: Dual decoder attention-based semantic segmentation networks for COVID-19 infection segmentation and classification using chest X-Ray images.
    Gopatoti A; Jayakumar R; Billa P; Patteeswaran V
    J Xray Sci Technol; 2024; 32(3):623-649. PubMed ID: 38607728
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A radiomics-boosted deep-learning model for COVID-19 and non-COVID-19 pneumonia classification using chest x-ray images.
    Hu Z; Yang Z; Lafata KJ; Yin FF; Wang C
    Med Phys; 2022 May; 49(5):3213-3222. PubMed ID: 35263458
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 26.