BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

402 related articles for article (PubMed ID: 33334578)

  • 1. Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study.
    Kim HE; Kim HH; Han BK; Kim KH; Han K; Nam H; Lee EH; Kim EK
    Lancet Digit Health; 2020 Mar; 2(3):e138-e148. PubMed ID: 33334578
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Artificial intelligence assistance for women who had spot compression view: reducing recall rates for digital mammography.
    Lee SE; Kim GR; Yoon JH; Han K; Son WJ; Shin HJ; Moon HJ
    Acta Radiol; 2023 May; 64(5):1808-1815. PubMed ID: 36426409
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms.
    Schaffter T; Buist DSM; Lee CI; Nikulin Y; Ribli D; Guan Y; Lotter W; Jie Z; Du H; Wang S; Feng J; Feng M; Kim HE; Albiol F; Albiol A; Morrell S; Wojna Z; Ahsen ME; Asif U; Jimeno Yepes A; Yohanandan S; Rabinovici-Cohen S; Yi D; Hoff B; Yu T; Chaibub Neto E; Rubin DL; Lindholm P; Margolies LR; McBride RB; Rothstein JH; Sieh W; Ben-Ari R; Harrer S; Trister A; Friend S; Norman T; Sahiner B; Strand F; Guinney J; Stolovitzky G; ; Mackey L; Cahoon J; Shen L; Sohn JH; Trivedi H; Shen Y; Buturovic L; Pereira JC; Cardoso JS; Castro E; Kalleberg KT; Pelka O; Nedjar I; Geras KJ; Nensa F; Goan E; Koitka S; Caballero L; Cox DD; Krishnaswamy P; Pandey G; Friedrich CM; Perrin D; Fookes C; Shi B; Cardoso Negrie G; Kawczynski M; Cho K; Khoo CS; Lo JY; Sorensen AG; Jung H
    JAMA Netw Open; 2020 Mar; 3(3):e200265. PubMed ID: 32119094
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Improving the Performance of Radiologists Using Artificial Intelligence-Based Detection Support Software for Mammography: A Multi-Reader Study.
    Lee JH; Kim KH; Lee EH; Ahn JS; Ryu JK; Park YM; Shin GW; Kim YJ; Choi HY
    Korean J Radiol; 2022 May; 23(5):505-516. PubMed ID: 35434976
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Improved Cancer Detection Using Artificial Intelligence: a Retrospective Evaluation of Missed Cancers on Mammography.
    Watanabe AT; Lim V; Vu HX; Chim R; Weise E; Liu J; Bradley WG; Comstock CE
    J Digit Imaging; 2019 Aug; 32(4):625-637. PubMed ID: 31011956
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Artificial intelligence-supported screen reading versus standard double reading in the Mammography Screening with Artificial Intelligence trial (MASAI): a clinical safety analysis of a randomised, controlled, non-inferiority, single-blinded, screening accuracy study.
    Lång K; Josefsson V; Larsson AM; Larsson S; Högberg C; Sartor H; Hofvind S; Andersson I; Rosso A
    Lancet Oncol; 2023 Aug; 24(8):936-944. PubMed ID: 37541274
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Population-wide evaluation of artificial intelligence and radiologist assessment of screening mammograms.
    Kühl J; Elhakim MT; Stougaard SW; Rasmussen BSB; Nielsen M; Gerke O; Larsen LB; Graumann O
    Eur Radiol; 2024 Jun; 34(6):3935-3946. PubMed ID: 37938386
    [TBL] [Abstract][Full Text] [Related]  

  • 8. External Evaluation of 3 Commercial Artificial Intelligence Algorithms for Independent Assessment of Screening Mammograms.
    Salim M; Wåhlin E; Dembrower K; Azavedo E; Foukakis T; Liu Y; Smith K; Eklund M; Strand F
    JAMA Oncol; 2020 Oct; 6(10):1581-1588. PubMed ID: 32852536
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Performance of artificial intelligence in 7533 consecutive prevalent screening mammograms from the BreastScreen Australia program.
    Waugh J; Evans J; Miocevic M; Lockie D; Aminzadeh P; Lynch A; Bell RJ
    Eur Radiol; 2024 Jun; 34(6):3947-3957. PubMed ID: 37955669
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Stand-Alone Use of Artificial Intelligence for Digital Mammography and Digital Breast Tomosynthesis Screening: A Retrospective Evaluation.
    Romero-Martín S; Elías-Cabot E; Raya-Povedano JL; Gubern-Mérida A; Rodríguez-Ruiz A; Álvarez-Benito M
    Radiology; 2022 Mar; 302(3):535-542. PubMed ID: 34904872
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Effect of artificial intelligence-based computer-aided diagnosis on the screening outcomes of digital mammography: a matched cohort study.
    Kim H; Choi JS; Kim K; Ko ES; Ko EY; Han BK
    Eur Radiol; 2023 Oct; 33(10):7186-7198. PubMed ID: 37188881
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Use of Artificial Intelligence for Reducing Unnecessary Recalls at Screening Mammography: A Simulation Study.
    Kim YS; Jang MJ; Lee SH; Kim SY; Ha SM; Kwon BR; Moon WK; Chang JM
    Korean J Radiol; 2022 Dec; 23(12):1241-1250. PubMed ID: 36447412
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Impact of AI for Digital Breast Tomosynthesis on Breast Cancer Detection and Interpretation Time.
    Park EK; Kwak S; Lee W; Choi JS; Kooi T; Kim EK
    Radiol Artif Intell; 2024 May; 6(3):e230318. PubMed ID: 38568095
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis.
    Leibig C; Brehmer M; Bunk S; Byng D; Pinker K; Umutlu L
    Lancet Digit Health; 2022 Jul; 4(7):e507-e519. PubMed ID: 35750400
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Artificial intelligence (AI) for breast cancer screening: BreastScreen population-based cohort study of cancer detection.
    Marinovich ML; Wylie E; Lotter W; Lund H; Waddell A; Madeley C; Pereira G; Houssami N
    EBioMedicine; 2023 Apr; 90():104498. PubMed ID: 36863255
    [TBL] [Abstract][Full Text] [Related]  

  • 16. An Artificial Intelligence-based Mammography Screening Protocol for Breast Cancer: Outcome and Radiologist Workload.
    Lauritzen AD; Rodríguez-Ruiz A; von Euler-Chelpin MC; Lynge E; Vejborg I; Nielsen M; Karssemeijer N; Lillholm M
    Radiology; 2022 Jul; 304(1):41-49. PubMed ID: 35438561
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Detection of Breast Cancer with Mammography: Effect of an Artificial Intelligence Support System.
    Rodríguez-Ruiz A; Krupinski E; Mordang JJ; Schilling K; Heywang-Köbrunner SH; Sechopoulos I; Mann RM
    Radiology; 2019 Feb; 290(2):305-314. PubMed ID: 30457482
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Impact of a Categorical AI System for Digital Breast Tomosynthesis on Breast Cancer Interpretation by Both General Radiologists and Breast Imaging Specialists.
    Kim JG; Haslam B; Diab AR; Sakhare A; Grisot G; Lee H; Holt J; Lee CI; Lotter W; Sorensen AG
    Radiol Artif Intell; 2024 Mar; 6(2):e230137. PubMed ID: 38323914
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study.
    Rodriguez-Ruiz A; Lång K; Gubern-Merida A; Teuwen J; Broeders M; Gennaro G; Clauser P; Helbich TH; Chevalier M; Mertelmeier T; Wallis MG; Andersson I; Zackrisson S; Sechopoulos I; Mann RM
    Eur Radiol; 2019 Sep; 29(9):4825-4832. PubMed ID: 30993432
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Artificial intelligence for breast cancer detection in screening mammography in Sweden: a prospective, population-based, paired-reader, non-inferiority study.
    Dembrower K; Crippa A; Colón E; Eklund M; Strand F;
    Lancet Digit Health; 2023 Oct; 5(10):e703-e711. PubMed ID: 37690911
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 21.