BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

282 related articles for article (PubMed ID: 33563200)

  • 1. Detection of Lung Cancer on Computed Tomography Using Artificial Intelligence Applications Developed by Deep Learning Methods and the Contribution of Deep Learning to the Classification of Lung Carcinoma.
    Aydın N; Çelik Ö; Aslan AF; Odabaş A; Dündar E; Şahin MC
    Curr Med Imaging; 2021; 17(9):1137-1141. PubMed ID: 33563200
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Automatic classification and detection of oral cancer in photographic images using deep learning algorithms.
    Warin K; Limprasert W; Suebnukarn S; Jinaporntham S; Jantana P
    J Oral Pathol Med; 2021 Oct; 50(9):911-918. PubMed ID: 34358372
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Contribution of artificial intelligence applications developed with the deep learning method to the diagnosis of COVID-19 pneumonia on computed tomography.
    Aydın N; Çelik Ö
    Tuberk Toraks; 2021 Dec; 69(4):486-491. PubMed ID: 34957742
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks.
    Horie Y; Yoshio T; Aoyama K; Yoshimizu S; Horiuchi Y; Ishiyama A; Hirasawa T; Tsuchida T; Ozawa T; Ishihara S; Kumagai Y; Fujishiro M; Maetani I; Fujisaki J; Tada T
    Gastrointest Endosc; 2019 Jan; 89(1):25-32. PubMed ID: 30120958
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Feature-shared adaptive-boost deep learning for invasiveness classification of pulmonary subsolid nodules in CT images.
    Wang J; Chen X; Lu H; Zhang L; Pan J; Bao Y; Su J; Qian D
    Med Phys; 2020 Apr; 47(4):1738-1749. PubMed ID: 32020649
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Diagnostic performance for pulmonary adenocarcinoma on CT: comparison of radiologists with and without three-dimensional convolutional neural network.
    Yanagawa M; Niioka H; Kusumoto M; Awai K; Tsubamoto M; Satoh Y; Miyata T; Yoshida Y; Kikuchi N; Hata A; Yamasaki S; Kido S; Nagahara H; Miyake J; Tomiyama N
    Eur Radiol; 2021 Apr; 31(4):1978-1986. PubMed ID: 33011879
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Lung cancer histology classification from CT images based on radiomics and deep learning models.
    Marentakis P; Karaiskos P; Kouloulias V; Kelekis N; Argentos S; Oikonomopoulos N; Loukas C
    Med Biol Eng Comput; 2021 Jan; 59(1):215-226. PubMed ID: 33411267
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Application of deep learning as a noninvasive tool to differentiate muscle-invasive bladder cancer and non-muscle-invasive bladder cancer with CT.
    Yang Y; Zou X; Wang Y; Ma X
    Eur J Radiol; 2021 Jun; 139():109666. PubMed ID: 33798819
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Toward an Expert Level of Lung Cancer Detection and Classification Using a Deep Convolutional Neural Network.
    Zhang C; Sun X; Dang K; Li K; Guo XW; Chang J; Yu ZQ; Huang FY; Wu YS; Liang Z; Liu ZY; Zhang XG; Gao XL; Huang SH; Qin J; Feng WN; Zhou T; Zhang YB; Fang WJ; Zhao MF; Yang XN; Zhou Q; Wu YL; Zhong WZ
    Oncologist; 2019 Sep; 24(9):1159-1165. PubMed ID: 30996009
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Artificial intelligence (AI) diagnostic tools: utilizing a convolutional neural network (CNN) to assess periodontal bone level radiographically-a retrospective study.
    Alotaibi G; Awawdeh M; Farook FF; Aljohani M; Aldhafiri RM; Aldhoayan M
    BMC Oral Health; 2022 Sep; 22(1):399. PubMed ID: 36100856
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Non-small cell lung cancer diagnosis aid with histopathological images using Explainable Deep Learning techniques.
    Civit-Masot J; Bañuls-Beaterio A; Domínguez-Morales M; Rivas-Pérez M; Muñoz-Saavedra L; Rodríguez Corral JM
    Comput Methods Programs Biomed; 2022 Nov; 226():107108. PubMed ID: 36113183
    [TBL] [Abstract][Full Text] [Related]  

  • 12. One-step algorithm for fast-track localization and multi-category classification of histological subtypes in lung cancer.
    Qi J; Deng Z; Sun G; Qian S; Liu L; Xu B
    Eur J Radiol; 2022 Sep; 154():110443. PubMed ID: 35901600
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Synthetic CT image generation of shape-controlled lung cancer using semi-conditional InfoGAN and its applicability for type classification.
    Toda R; Teramoto A; Tsujimoto M; Toyama H; Imaizumi K; Saito K; Fujita H
    Int J Comput Assist Radiol Surg; 2021 Feb; 16(2):241-251. PubMed ID: 33428062
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep CNN models for pulmonary nodule classification: Model modification, model integration, and transfer learning.
    Zhao X; Qi S; Zhang B; Ma H; Qian W; Yao Y; Sun J
    J Xray Sci Technol; 2019; 27(4):615-629. PubMed ID: 31227682
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deep learning predicts epidermal growth factor receptor mutation subtypes in lung adenocarcinoma.
    Song J; Ding C; Huang Q; Luo T; Xu X; Chen Z; Li S
    Med Phys; 2021 Dec; 48(12):7891-7899. PubMed ID: 34669994
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Multi-task learning-based histologic subtype classification of non-small cell lung cancer.
    Chen K; Wang M; Song Z
    Radiol Med; 2023 May; 128(5):537-543. PubMed ID: 36976403
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep learning-based CAD schemes for the detection and classification of lung nodules from CT images: A survey.
    Mastouri R; Khlifa N; Neji H; Hantous-Zannad S
    J Xray Sci Technol; 2020; 28(4):591-617. PubMed ID: 32568165
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep learning classification of lung cancer histology using CT images.
    Chaunzwa TL; Hosny A; Xu Y; Shafer A; Diao N; Lanuti M; Christiani DC; Mak RH; Aerts HJWL
    Sci Rep; 2021 Mar; 11(1):5471. PubMed ID: 33727623
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Automated Lung Nodule Detection and Classification Using Deep Learning Combined with Multiple Strategies.
    Nasrullah N; Sang J; Alam MS; Mateen M; Cai B; Hu H
    Sensors (Basel); 2019 Aug; 19(17):. PubMed ID: 31466261
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A deep learning framework for automatic detection of arbitrarily shaped fiducial markers in intrafraction fluoroscopic images.
    Mylonas A; Keall PJ; Booth JT; Shieh CC; Eade T; Poulsen PR; Nguyen DT
    Med Phys; 2019 May; 46(5):2286-2297. PubMed ID: 30929254
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.