These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

121 related articles for article (PubMed ID: 34376926)

  • 1. C+EffxNet: A novel hybrid approach for COVID-19 diagnosis on CT images based on CBAM and EfficientNet.
    Canayaz M
    Chaos Solitons Fractals; 2021 Oct; 151():111310. PubMed ID: 34376926
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep learning-based meta-classifier approach for COVID-19 classification using CT scan and chest X-ray images.
    Ravi V; Narasimhan H; Chakraborty C; Pham TD
    Multimed Syst; 2022; 28(4):1401-1415. PubMed ID: 34248292
    [TBL] [Abstract][Full Text] [Related]  

  • 3. An automated COVID-19 detection based on fused dynamic exemplar pyramid feature extraction and hybrid feature selection using deep learning.
    Ozyurt F; Tuncer T; Subasi A
    Comput Biol Med; 2021 May; 132():104356. PubMed ID: 33799219
    [TBL] [Abstract][Full Text] [Related]  

  • 4. CoV2-Detect-Net: Design of COVID-19 prediction model based on hybrid DE-PSO with SVM using chest X-ray images.
    Dixit A; Mani A; Bansal R
    Inf Sci (N Y); 2021 Sep; 571():676-692. PubMed ID: 33840820
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Effect of image transformation on EfficientNet model for COVID-19 CT image classification.
    Shamila Ebenezer A; Deepa Kanmani S; Sivakumar M; Jeba Priya S
    Mater Today Proc; 2022; 51():2512-2519. PubMed ID: 34926175
    [TBL] [Abstract][Full Text] [Related]  

  • 6. The investigation of multiresolution approaches for chest X-ray image based COVID-19 detection.
    Ismael AM; Şengür A
    Health Inf Sci Syst; 2020 Dec; 8(1):29. PubMed ID: 33014355
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Accurately Differentiating Between Patients With COVID-19, Patients With Other Viral Infections, and Healthy Individuals: Multimodal Late Fusion Learning Approach.
    Xu M; Ouyang L; Han L; Sun K; Yu T; Li Q; Tian H; Safarnejad L; Zhang H; Gao Y; Bao FS; Chen Y; Robinson P; Ge Y; Zhu B; Liu J; Chen S
    J Med Internet Res; 2021 Jan; 23(1):e25535. PubMed ID: 33404516
    [TBL] [Abstract][Full Text] [Related]  

  • 8. COVID-AleXception: A Deep Learning Model Based on a Deep Feature Concatenation Approach for the Detection of COVID-19 from Chest X-ray Images.
    Ayadi M; Ksibi A; Al-Rasheed A; Soufiene BO
    Healthcare (Basel); 2022 Oct; 10(10):. PubMed ID: 36292519
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A bi-stage feature selection approach for COVID-19 prediction using chest CT images.
    Sen S; Saha S; Chatterjee S; Mirjalili S; Sarkar R
    Appl Intell (Dordr); 2021; 51(12):8985-9000. PubMed ID: 34764594
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Feature selection using ant colony optimization with tandem-run recruitment to diagnose bronchitis from CT scan images.
    Sweetlin JD; Nehemiah HK; Kannan A
    Comput Methods Programs Biomed; 2017 Jul; 145():115-125. PubMed ID: 28552117
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Local binary pattern and deep learning feature extraction fusion for COVID-19 detection on computed tomography images.
    Mubarak AS; Serte S; Al-Turjman F; Ameen ZS; Ozsoz M
    Expert Syst; 2022 Mar; 39(3):e12842. PubMed ID: 34898796
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Transfer learning-based ensemble support vector machine model for automated COVID-19 detection using lung computerized tomography scan data.
    Singh M; Bansal S; Ahuja S; Dubey RK; Panigrahi BK; Dey N
    Med Biol Eng Comput; 2021 Apr; 59(4):825-839. PubMed ID: 33738639
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Diagnosis of musculoskeletal abnormalities based on improved lightweight network for multiple model fusion.
    Zeng Z; Song C; Liu Q; Yi S; Zhu Y
    Math Biosci Eng; 2024 Jan; 21(1):582-601. PubMed ID: 38303435
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Machine Learning with Quantum Seagull Optimization Model for COVID-19 Chest X-Ray Image Classification.
    Ragab M; Alshehri S; Alhakamy NA; Alsaggaf W; Alhadrami HA; Alyami J
    J Healthc Eng; 2022; 2022():6074538. PubMed ID: 35368940
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Screening of COVID-19 based on the extracted radiomics features from chest CT images.
    Rezaeijo SM; Abedi-Firouzjah R; Ghorvei M; Sarnameh S
    J Xray Sci Technol; 2021; 29(2):229-243. PubMed ID: 33612539
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Classification of Coronavirus (COVID-19) from X-ray and CT images using shrunken features.
    Öztürk Ş; Özkaya U; Barstuğan M
    Int J Imaging Syst Technol; 2021 Mar; 31(1):5-15. PubMed ID: 32904960
    [TBL] [Abstract][Full Text] [Related]  

  • 17. DMs-MAFM+EfficientNet: a hybrid model for predicting dysthyroid optic neuropathy.
    Wu C; Li S; Liu X; Jiang F; Shi B
    Med Biol Eng Comput; 2022 Nov; 60(11):3217-3230. PubMed ID: 36129645
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Automated detection of Covid-19 disease using deep fused features from chest radiography images.
    Uçar E; Atila Ü; Uçar M; Akyol K
    Biomed Signal Process Control; 2021 Aug; 69():102862. PubMed ID: 34131433
    [TBL] [Abstract][Full Text] [Related]  

  • 19. COVID-19 diagnosis using state-of-the-art CNN architecture features and Bayesian Optimization.
    Aslan MF; Sabanci K; Durdu A; Unlersen MF
    Comput Biol Med; 2022 Mar; 142():105244. PubMed ID: 35077936
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Machine learning-based automatic detection of novel coronavirus (COVID-19) disease.
    Bhargava A; Bansal A; Goyal V
    Multimed Tools Appl; 2022; 81(10):13731-13750. PubMed ID: 35221781
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.