BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

210 related articles for article (PubMed ID: 37660400)

  • 21. AI-based Strategies to Reduce Workload in Breast Cancer Screening with Mammography and Tomosynthesis: A Retrospective Evaluation.
    Raya-Povedano JL; Romero-Martín S; Elías-Cabot E; Gubern-Mérida A; Rodríguez-Ruiz A; Álvarez-Benito M
    Radiology; 2021 Jul; 300(1):57-65. PubMed ID: 33944627
    [TBL] [Abstract][Full Text] [Related]  

  • 22. 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]  

  • 23. Radiologist Preferences for Artificial Intelligence-Based Decision Support During Screening Mammography Interpretation.
    Hendrix N; Lowry KP; Elmore JG; Lotter W; Sorensen G; Hsu W; Liao GJ; Parsian S; Kolb S; Naeim A; Lee CI
    J Am Coll Radiol; 2022 Oct; 19(10):1098-1110. PubMed ID: 35970474
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Artificial intelligence (AI) to enhance breast cancer screening: protocol for population-based cohort study of cancer detection.
    Marinovich ML; Wylie E; Lotter W; Pearce A; Carter SM; Lund H; Waddell A; Kim JG; Pereira GF; Lee CI; Zackrisson S; Brennan M; Houssami N
    BMJ Open; 2022 Jan; 12(1):e054005. PubMed ID: 34980622
    [TBL] [Abstract][Full Text] [Related]  

  • 25. 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]  

  • 26. Artificial Intelligence for Reducing Workload in Breast Cancer Screening with Digital Breast Tomosynthesis.
    Shoshan Y; Bakalo R; Gilboa-Solomon F; Ratner V; Barkan E; Ozery-Flato M; Amit M; Khapun D; Ambinder EB; Oluyemi ET; Panigrahi B; DiCarlo PA; Rosen-Zvi M; Mullen LA
    Radiology; 2022 Apr; 303(1):69-77. PubMed ID: 35040677
    [TBL] [Abstract][Full Text] [Related]  

  • 27. 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]  

  • 28. Artificial intelligence in BreastScreen Norway: a retrospective analysis of a cancer-enriched sample including 1254 breast cancer cases.
    Koch HW; Larsen M; Bartsch H; Kurz KD; Hofvind S
    Eur Radiol; 2023 May; 33(5):3735-3743. PubMed ID: 36917260
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists.
    Rodriguez-Ruiz A; Lång K; Gubern-Merida A; Broeders M; Gennaro G; Clauser P; Helbich TH; Chevalier M; Tan T; Mertelmeier T; Wallis MG; Andersson I; Zackrisson S; Mann RM; Sechopoulos I
    J Natl Cancer Inst; 2019 Sep; 111(9):916-922. PubMed ID: 30834436
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Possible strategies for use of artificial intelligence in screen-reading of mammograms, based on retrospective data from 122,969 screening examinations.
    Larsen M; Aglen CF; Hoff SR; Lund-Hanssen H; Hofvind S
    Eur Radiol; 2022 Dec; 32(12):8238-8246. PubMed ID: 35704111
    [TBL] [Abstract][Full Text] [Related]  

  • 31. AI for reading screening mammograms: the need for circumspection.
    Autier P; Burrion JB; Grivegnée AR
    Eur Radiol; 2020 Sep; 30(9):4783-4784. PubMed ID: 32318845
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study.
    van Winkel SL; Rodríguez-Ruiz A; Appelman L; Gubern-Mérida A; Karssemeijer N; Teuwen J; Wanders AJT; Sechopoulos I; Mann RM
    Eur Radiol; 2021 Nov; 31(11):8682-8691. PubMed ID: 33948701
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Screening in Patients With Dense Breasts: Comparison of Mammography, Artificial Intelligence, and Supplementary Ultrasound.
    Lee SE; Yoon JH; Son NH; Han K; Moon HJ
    AJR Am J Roentgenol; 2024 Jan; 222(1):e2329655. PubMed ID: 37493324
    [No Abstract]   [Full Text] [Related]  

  • 34. Artificial Intelligence in Screening Mammography: A Population Survey of Women's Preferences.
    Ongena YP; Yakar D; Haan M; Kwee TC
    J Am Coll Radiol; 2021 Jan; 18(1 Pt A):79-86. PubMed ID: 33058789
    [TBL] [Abstract][Full Text] [Related]  

  • 35. 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]  

  • 36. Effect of integrating digital breast tomosynthesis (3D-mammography) with acquired or synthetic 2D-mammography on radiologists' true-positive and false-positive detection in a population screening trial: A descriptive study.
    Bernardi D; Li T; Pellegrini M; Macaskill P; Valentini M; Fantò C; Ostillio L; Houssami N
    Eur J Radiol; 2018 Sep; 106():26-31. PubMed ID: 30150047
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Using deep learning to assist readers during the arbitration process: a lesion-based retrospective evaluation of breast cancer screening performance.
    Kerschke L; Weigel S; Rodriguez-Ruiz A; Karssemeijer N; Heindel W
    Eur Radiol; 2022 Feb; 32(2):842-852. PubMed ID: 34383147
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Range of Radiologist Performance in a Population-based Screening Cohort of 1 Million Digital Mammography Examinations.
    Salim M; Dembrower K; Eklund M; Lindholm P; Strand F
    Radiology; 2020 Oct; 297(1):33-39. PubMed ID: 32720866
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Effect of integrating 3D-mammography (digital breast tomosynthesis) with 2D-mammography on radiologists' true-positive and false-positive detection in a population breast screening trial.
    Bernardi D; Caumo F; Macaskill P; Ciatto S; Pellegrini M; Brunelli S; Tuttobene P; Bricolo P; Fantò C; Valentini M; Montemezzi S; Houssami N
    Eur J Cancer; 2014 May; 50(7):1232-8. PubMed ID: 24582915
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Impact of Artificial Intelligence Decision Support Using Deep Learning on Breast Cancer Screening Interpretation with Single-View Wide-Angle Digital Breast Tomosynthesis.
    Pinto MC; Rodriguez-Ruiz A; Pedersen K; Hofvind S; Wicklein J; Kappler S; Mann RM; Sechopoulos I
    Radiology; 2021 Sep; 300(3):529-536. PubMed ID: 34227882
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 11.