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Journal Abstract Search

196 related items for PubMed ID: 36719681

  • 1. Development and Validation of a Deep Learning-Based Synthetic Bone-Suppressed Model for Pulmonary Nodule Detection in Chest Radiographs.
    Kim H, Lee KH, Han K, Lee JW, Kim JY, Im DJ, Hong YJ, Choi BW, Hur J.
    JAMA Netw Open; 2023 Jan 03; 6(1):e2253820. PubMed ID: 36719681
    [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 01; 3(9):e2017135. PubMed ID: 32970157
    [Abstract] [Full Text] [Related]

  • 3. Development and Validation of Deep Learning-based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs.
    Nam JG, Park S, Hwang EJ, Lee JH, Jin KN, Lim KY, Vu TH, Sohn JH, Hwang S, Goo JM, Park CM.
    Radiology; 2019 Jan 01; 290(1):218-228. PubMed ID: 30251934
    [Abstract] [Full Text] [Related]

  • 4. Development and Validation of a Deep Learning-Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs.
    Hwang EJ, Park S, Jin KN, Kim JI, Choi SY, Lee JH, Goo JM, Aum J, Yim JJ, Cohen JG, Ferretti GR, Park CM, DLAD Development and Evaluation Group.
    JAMA Netw Open; 2019 Mar 01; 2(3):e191095. PubMed ID: 30901052
    [Abstract] [Full Text] [Related]

  • 5. Deep Convolutional Neural Network-based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs.
    Sim Y, Chung MJ, Kotter E, Yune S, Kim M, Do S, Han K, Kim H, Yang S, Lee DJ, Choi BW.
    Radiology; 2020 Jan 01; 294(1):199-209. PubMed ID: 31714194
    [Abstract] [Full Text] [Related]

  • 6. Optimal matrix size of chest radiographs for computer-aided detection on lung nodule or mass with deep learning.
    Kim YG, Lee SM, Lee KH, Jang R, Seo JB, Kim N.
    Eur Radiol; 2020 Sep 01; 30(9):4943-4951. PubMed ID: 32350657
    [Abstract] [Full Text] [Related]

  • 7. AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset.
    Yoo H, Lee SH, Arru CD, Doda Khera R, Singh R, Siebert S, Kim D, Lee Y, Park JH, Eom HJ, Digumarthy SR, Kalra MK.
    Eur Radiol; 2021 Dec 01; 31(12):9664-9674. PubMed ID: 34089072
    [Abstract] [Full Text] [Related]

  • 8. Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists.
    Rajpurkar P, Irvin J, Ball RL, Zhu K, Yang B, Mehta H, Duan T, Ding D, Bagul A, Langlotz CP, Patel BN, Yeom KW, Shpanskaya K, Blankenberg FG, Seekins J, Amrhein TJ, Mong DA, Halabi SS, Zucker EJ, Ng AY, Lungren MP.
    PLoS Med; 2018 Nov 01; 15(11):e1002686. PubMed ID: 30457988
    [Abstract] [Full Text] [Related]

  • 9. Better performance of deep learning pulmonary nodule detection using chest radiography with pixel level labels in reference to computed tomography: data quality matters.
    Kim JY, Ryu WS, Kim D, Kim EY.
    Sci Rep; 2024 Jul 10; 14(1):15967. PubMed ID: 38987309
    [Abstract] [Full Text] [Related]

  • 10. An Artificial Intelligence-Based Chest X-ray Model on Human Nodule Detection Accuracy From a Multicenter Study.
    Homayounieh F, Digumarthy S, Ebrahimian S, Rueckel J, Hoppe BF, Sabel BO, Conjeti S, Ridder K, Sistermanns M, Wang L, Preuhs A, Ghesu F, Mansoor A, Moghbel M, Botwin A, Singh R, Cartmell S, Patti J, Huemmer C, Fieselmann A, Joerger C, Mirshahzadeh N, Muse V, Kalra M.
    JAMA Netw Open; 2021 Dec 01; 4(12):e2141096. PubMed ID: 34964851
    [Abstract] [Full Text] [Related]

  • 11. Identifying pulmonary nodules or masses on chest radiography using deep learning: external validation and strategies to improve clinical practice.
    Liang CH, Liu YC, Wu MT, Garcia-Castro F, Alberich-Bayarri A, Wu FZ.
    Clin Radiol; 2020 Jan 01; 75(1):38-45. PubMed ID: 31521323
    [Abstract] [Full Text] [Related]

  • 12. Bone suppressed images improve radiologists' detection performance for pulmonary nodules in chest radiographs.
    Schalekamp S, van Ginneken B, Meiss L, Peters-Bax L, Quekel LG, Snoeren MM, Tiehuis AM, Wittenberg R, Karssemeijer N, Schaefer-Prokop CM.
    Eur J Radiol; 2013 Dec 01; 82(12):2399-405. PubMed ID: 24113431
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  • 14. Lung nodule detection in chest X-rays using synthetic ground-truth data comparing CNN-based diagnosis to human performance.
    Schultheiss M, Schmette P, Bodden J, Aichele J, Müller-Leisse C, Gassert FG, Gassert FT, Gawlitza JF, Hofmann FC, Sasse D, von Schacky CE, Ziegelmayer S, De Marco F, Renger B, Makowski MR, Pfeiffer F, Pfeiffer D.
    Sci Rep; 2021 Aug 04; 11(1):15857. PubMed ID: 34349135
    [Abstract] [Full Text] [Related]

  • 15. Value of a deep learning-based algorithm for detecting Lung-RADS category 4 nodules on chest radiographs in a health checkup population: estimation of the sample size for a randomized controlled trial.
    Nam JG, Kim HJ, Lee EH, Hong W, Park J, Hwang EJ, Park CM, Goo JM.
    Eur Radiol; 2022 Jan 04; 32(1):213-222. PubMed ID: 34264351
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  • 17. Lung nodule detection by microdose CT versus chest radiography (standard and dual-energy subtracted).
    Ebner L, Bütikofer Y, Ott D, Huber A, Landau J, Roos JE, Heverhagen JT, Christe A.
    AJR Am J Roentgenol; 2015 Apr 04; 204(4):727-35. PubMed ID: 25794062
    [Abstract] [Full Text] [Related]

  • 18. Dual energy subtraction digital radiography improves performance of a next generation computer-aided detection program.
    Balkman JD, Mehandru S, DuPont E, Novak RD, Gilkeson RC.
    J Thorac Imaging; 2010 Feb 04; 25(1):41-7. PubMed ID: 20160602
    [Abstract] [Full Text] [Related]

  • 19. Diagnosis of Coronavirus Disease 2019 Pneumonia by Using Chest Radiography: Value of Artificial Intelligence.
    Zhang R, Tie X, Qi Z, Bevins NB, Zhang C, Griner D, Song TK, Nadig JD, Schiebler ML, Garrett JW, Li K, Reeder SB, Chen GH.
    Radiology; 2021 Feb 04; 298(2):E88-E97. PubMed ID: 32969761
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