BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

815 related articles for article (PubMed ID: 34964851)

  • 21. Evaluation of computer-aided diagnosis (CAD) software for the detection of lung nodules on multidetector row computed tomography (MDCT): JAFROC study for the improvement in radiologists' diagnostic accuracy.
    Hirose T; Nitta N; Shiraishi J; Nagatani Y; Takahashi M; Murata K
    Acad Radiol; 2008 Dec; 15(12):1505-12. PubMed ID: 19000867
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Effect of Human-AI Interaction on Detection of Malignant Lung Nodules on Chest Radiographs.
    Lee JH; Hong H; Nam G; Hwang EJ; Park CM
    Radiology; 2023 Jun; 307(5):e222976. PubMed ID: 37367443
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Deep learning-based automatic detection for pulmonary nodules on chest radiographs: The relationship with background lung condition, nodule characteristics, and location.
    Ueno M; Yoshida K; Takamatsu A; Kobayashi T; Aoki T; Gabata T
    Eur J Radiol; 2023 Sep; 166():111002. PubMed ID: 37499478
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Deep Learning Assistance Closes the Accuracy Gap in Fracture Detection Across Clinician Types.
    Anderson PG; Baum GL; Keathley N; Sicular S; Venkatesh S; Sharma A; Daluiski A; Potter H; Hotchkiss R; Lindsey RV; Jones RM
    Clin Orthop Relat Res; 2023 Mar; 481(3):580-588. PubMed ID: 36083847
    [TBL] [Abstract][Full Text] [Related]  

  • 25. A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images.
    Gong J; Liu J; Hao W; Nie S; Zheng B; Wang S; Peng W
    Eur Radiol; 2020 Apr; 30(4):1847-1855. PubMed ID: 31811427
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Diagnostic performance of artificial intelligence for pediatric pulmonary nodule detection in computed tomography of the chest.
    Salman R; Nguyen HN; Sher AC; Hallam KA; Seghers VJ; Sammer MBK
    Clin Imaging; 2023 Sep; 101():50-55. PubMed ID: 37301051
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Retrospectively assessing evaluation and management of artificial-intelligence detected nodules on uninterpreted chest radiographs in the era of radiologists shortage.
    Kirshenboim Z; Gilat EK; Carl L; Bekker E; Tau N; Klug M; Konen E; Marom EM
    Eur J Radiol; 2024 Jan; 170():111241. PubMed ID: 38042019
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Commercially available computer-aided detection system for pulmonary nodules on thin-section images using 64 detectors-row CT: preliminary study of 48 cases.
    Yanagawa M; Honda O; Yoshida S; Ono Y; Inoue A; Daimon T; Sumikawa H; Mihara N; Johkoh T; Tomiyama N; Nakamura H
    Acad Radiol; 2009 Aug; 16(8):924-33. PubMed ID: 19394873
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Validation of a deep learning computer aided system for CT based lung nodule detection, classification, and growth rate estimation in a routine clinical population.
    Murchison JT; Ritchie G; Senyszak D; Nijwening JH; van Veenendaal G; Wakkie J; van Beek EJR
    PLoS One; 2022; 17(5):e0266799. PubMed ID: 35511758
    [TBL] [Abstract][Full Text] [Related]  

  • 30. 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; 82(12):2399-405. PubMed ID: 24113431
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Short-term Reproducibility of Pulmonary Nodule and Mass Detection in Chest Radiographs: Comparison among Radiologists and Four Different Computer-Aided Detections with Convolutional Neural Net.
    Kim YG; Cho Y; Wu CJ; Park S; Jung KH; Seo JB; Lee HJ; Hwang HJ; Lee SM; Kim N
    Sci Rep; 2019 Dec; 9(1):18738. PubMed ID: 31822774
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Performance and reading time of lung nodule identification on multidetector CT with or without an artificial intelligence-powered computer-aided detection system.
    Hsu HH; Ko KH; Chou YC; Wu YC; Chiu SH; Chang CK; Chang WC
    Clin Radiol; 2021 Aug; 76(8):626.e23-626.e32. PubMed ID: 34023068
    [TBL] [Abstract][Full Text] [Related]  

  • 33. 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; 290(1):218-228. PubMed ID: 30251934
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Integration of Artificial Intelligence Decision Aids to Reduce Workload and Enhance Efficiency in Thyroid Nodule Management.
    Tong WJ; Wu SH; Cheng MQ; Huang H; Liang JY; Li CQ; Guo HL; He DN; Liu YH; Xiao H; Hu HT; Ruan SM; Li MD; Lu MD; Wang W
    JAMA Netw Open; 2023 May; 6(5):e2313674. PubMed ID: 37191957
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT.
    Sourlos N; Pelgrim G; Wisselink HJ; Yang X; de Jonge G; Rook M; Prokop M; Sidorenkov G; van Tuinen M; Vliegenthart R; van Ooijen PMA
    Eur Radiol Exp; 2024 May; 8(1):63. PubMed ID: 38764066
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Evaluation of a real-time interactive pulmonary nodule analysis system on chest digital radiographic images: a prospective study.
    van Beek EJ; Mullan B; Thompson B
    Acad Radiol; 2008 May; 15(5):571-5. PubMed ID: 18423313
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Development of a novel artificial intelligence algorithm to detect pulmonary nodules on chest radiography.
    Higuchi M; Nagata T; Iwabuchi K; Sano A; Maekawa H; Idaka T; Yamasaki M; Seko C; Sato A; Suzuki J; Anzai Y; Yabuki T; Saito T; Suzuki H
    Fukushima J Med Sci; 2023 Nov; 69(3):177-183. PubMed ID: 37853640
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Computer-aided detection (CAD) in lung cancer screening at chest MDCT: ROC analysis of CAD versus radiologist performance.
    Fraioli F; Bertoletti L; Napoli A; Pediconi F; Calabrese FA; Masciangelo R; Catalano C; Passariello R
    J Thorac Imaging; 2007 Aug; 22(3):241-6. PubMed ID: 17721333
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Robust explanation supervision for false positive reduction in pulmonary nodule detection.
    Zhao Q; Chang CW; Yang X; Zhao L
    Med Phys; 2024 Mar; 51(3):1687-1701. PubMed ID: 38224306
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Computer-aided diagnosis for the detection and classification of lung cancers on chest radiographs ROC analysis of radiologists' performance.
    Shiraishi J; Abe H; Li F; Engelmann R; MacMahon H; Doi K
    Acad Radiol; 2006 Aug; 13(8):995-1003. PubMed ID: 16843852
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 41.