BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

320 related articles for article (PubMed ID: 32166491)

  • 1. Artificial intelligence and radiomics enhance the positive predictive value of digital chest tomosynthesis for lung cancer detection within SOS clinical trial.
    Chauvie S; De Maggi A; Baralis I; Dalmasso F; Berchialla P; Priotto R; Violino P; Mazza F; Melloni G; Grosso M;
    Eur Radiol; 2020 Jul; 30(7):4134-4140. PubMed ID: 32166491
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Validation of a Deep Learning Algorithm for the Detection of Malignant Pulmonary Nodules in Chest Radiographs.
    Yoo H; Kim KH; Singh R; Digumarthy SR; Kalra MK
    JAMA Netw Open; 2020 Sep; 3(9):e2017135. PubMed ID: 32970157
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Sensitivity of Thoracic Digital Tomosynthesis (DTS) for the Identification of Lung Nodules.
    Langer SG; Graner BD; Schueler BA; Fetterly KA; Kofler JM; Mandrekar JN; Bartholmai BJ
    J Digit Imaging; 2016 Feb; 29(1):141-7. PubMed ID: 26349914
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Comparison of digital tomosynthesis and computed tomography for lung nodule detection in SOS screening program.
    Grosso M; Priotto R; Ghirardo D; Talenti A; Roberto E; Bertolaccini L; Terzi A; Chauvie S;
    Radiol Med; 2017 Aug; 122(8):568-574. PubMed ID: 28429205
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Localized thin-section CT with radiomics feature extraction and machine learning to classify early-detected pulmonary nodules from lung cancer screening.
    Tu SJ; Wang CW; Pan KT; Wu YC; Wu CT
    Phys Med Biol; 2018 Mar; 63(6):065005. PubMed ID: 29446758
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Detection of Subsolid Nodules in Lung Cancer Screening: Complementary Sensitivity of Visual Reading and Computer-Aided Diagnosis.
    Silva M; Schaefer-Prokop CM; Jacobs C; Capretti G; Ciompi F; van Ginneken B; Pastorino U; Sverzellati N
    Invest Radiol; 2018 Aug; 53(8):441-449. PubMed ID: 29543693
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Added Value of Computer-aided CT Image Features for Early Lung Cancer Diagnosis with Small Pulmonary Nodules: A Matched Case-Control Study.
    Huang P; Park S; Yan R; Lee J; Chu LC; Lin CT; Hussien A; Rathmell J; Thomas B; Chen C; Hales R; Ettinger DS; Brock M; Hu P; Fishman EK; Gabrielson E; Lam S
    Radiology; 2018 Jan; 286(1):286-295. PubMed ID: 28872442
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Comparison Between Radiological Semantic Features and Lung-RADS in Predicting Malignancy of Screen-Detected Lung Nodules in the National Lung Screening Trial.
    Li Q; Balagurunathan Y; Liu Y; Qi J; Schabath MB; Ye Z; Gillies RJ
    Clin Lung Cancer; 2018 Mar; 19(2):148-156.e3. PubMed ID: 29137847
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Machine learning approach for distinguishing malignant and benign lung nodules utilizing standardized perinodular parenchymal features from CT.
    Uthoff J; Stephens MJ; Newell JD; Hoffman EA; Larson J; Koehn N; De Stefano FA; Lusk CM; Wenzlaff AS; Watza D; Neslund-Dudas C; Carr LL; Lynch DA; Schwartz AG; Sieren JC
    Med Phys; 2019 Jul; 46(7):3207-3216. PubMed ID: 31087332
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Comparison of prediction models with radiological semantic features and radiomics in lung cancer diagnosis of the pulmonary nodules: a case-control study.
    Wu W; Pierce LA; Zhang Y; Pipavath SNJ; Randolph TW; Lastwika KJ; Lampe PD; Houghton AM; Liu H; Xia L; Kinahan PE
    Eur Radiol; 2019 Nov; 29(11):6100-6108. PubMed ID: 31115618
    [TBL] [Abstract][Full Text] [Related]  

  • 11. CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma.
    Jiang C; Luo Y; Yuan J; You S; Chen Z; Wu M; Wang G; Gong J
    Eur Radiol; 2020 Jul; 30(7):4050-4057. PubMed ID: 32112116
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Automated detection of lung nodules and coronary artery calcium using artificial intelligence on low-dose CT scans for lung cancer screening: accuracy and prognostic value.
    Chamberlin J; Kocher MR; Waltz J; Snoddy M; Stringer NFC; Stephenson J; Sahbaee P; Sharma P; Rapaka S; Schoepf UJ; Abadia AF; Sperl J; Hoelzer P; Mercer M; Somayaji N; Aquino G; Burt JR
    BMC Med; 2021 Mar; 19(1):55. PubMed ID: 33658025
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A Novel Hybrid Feature Extraction Model for Classification on Pulmonary Nodules.
    Kailasam SP; Sathik MM
    Asian Pac J Cancer Prev; 2019 Feb; 20(2):457-468. PubMed ID: 30803208
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Shape-based computer-aided detection of lung nodules in thoracic CT images.
    Ye X; Lin X; Dehmeshki J; Slabaugh G; Beddoe G
    IEEE Trans Biomed Eng; 2009 Jul; 56(7):1810-20. PubMed ID: 19527950
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Detection of pulmonary nodules based on a multiscale feature 3D U-Net convolutional neural network of transfer learning.
    Tang S; Yang M; Bai J
    PLoS One; 2020; 15(8):e0235672. PubMed ID: 32845877
    [TBL] [Abstract][Full Text] [Related]  

  • 16. The value of digital tomosynthesis of the chest as a problem-solving tool for suspected pulmonary nodules and hilar lesions detected on chest radiography.
    Galea A; Dubbins P; Riordan R; Adlan T; Roobottom C; Gay D
    Eur J Radiol; 2015 May; 84(5):1012-8. PubMed ID: 25757629
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: localized search method based on anatomical classification.
    Shiraishi J; Li Q; Suzuki K; Engelmann R; Doi K
    Med Phys; 2006 Jul; 33(7):2642-53. PubMed ID: 16898468
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Clinical Impact and Generalizability of a Computer-Assisted Diagnostic Tool to Risk-Stratify Lung Nodules With CT.
    Adams SJ; Madtes DK; Burbridge B; Johnston J; Goldberg IG; Siegel EL; Babyn P; Nair VS; Calhoun ME
    J Am Coll Radiol; 2023 Feb; 20(2):232-242. PubMed ID: 36064040
    [TBL] [Abstract][Full Text] [Related]  

  • 19. One-view breast tomosynthesis versus two-view mammography in the Malmö Breast Tomosynthesis Screening Trial (MBTST): a prospective, population-based, diagnostic accuracy study.
    Zackrisson S; Lång K; Rosso A; Johnson K; Dustler M; Förnvik D; Förnvik H; Sartor H; Timberg P; Tingberg A; Andersson I
    Lancet Oncol; 2018 Nov; 19(11):1493-1503. PubMed ID: 30322817
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Radiomics analysis of pulmonary nodules in low-dose CT for early detection of lung cancer.
    Choi W; Oh JH; Riyahi S; Liu CJ; Jiang F; Chen W; White C; Rimner A; Mechalakos JG; Deasy JO; Lu W
    Med Phys; 2018 Apr; 45(4):1537-1549. PubMed ID: 29457229
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.