283 related articles for article (PubMed ID: 32876835)
1. Identifying normal mammograms in a large screening population using artificial intelligence.
Lång K; Dustler M; Dahlblom V; Åkesson A; Andersson I; Zackrisson S
Eur Radiol; 2021 Mar; 31(3):1687-1692. PubMed ID: 32876835
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. 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]
5. Breast cancer screening with digital breast tomosynthesis: comparison of different reading strategies implementing artificial intelligence.
Dahlblom V; Dustler M; Tingberg A; Zackrisson S
Eur Radiol; 2023 May; 33(5):3754-3765. PubMed ID: 36502459
[TBL] [Abstract][Full Text] [Related]
6. Can artificial intelligence reduce the interval cancer rate in mammography screening?
Lång K; Hofvind S; Rodríguez-Ruiz A; Andersson I
Eur Radiol; 2021 Aug; 31(8):5940-5947. PubMed ID: 33486604
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. Performance of an Artificial Intelligence System for Breast Cancer Detection on Screening Mammograms from BreastScreen Norway.
Larsen M; Olstad CF; Lee CI; Hovda T; Hoff SR; Martiniussen MA; Mikalsen KØ; Lund-Hanssen H; Solli HS; Silberhorn M; Sulheim ÅØ; Auensen S; Nygård JF; Hofvind S
Radiol Artif Intell; 2024 May; 6(3):e230375. PubMed ID: 38597784
[TBL] [Abstract][Full Text] [Related]
10. Use of novel artificial intelligence computer-assisted detection (AI-CAD) for screening mammography: an analysis of 17,884 consecutive two-view full-field digital mammography screening exams.
Heywang-Köbrunner SH; Hacker A; Jänsch A; Hertlein M; Mieskes C; Elsner S; Sinnatamby R; Katalinic A
Acta Radiol; 2023 Oct; 64(10):2697-2703. PubMed ID: 37642981
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. A Semiautonomous Deep Learning System to Reduce False Positives in Screening Mammography.
Pedemonte S; Tsue T; Mombourquette B; Truong Vu YN; Matthews T; Morales Hoil R; Shah M; Ghare N; Zingman-Daniels N; Holley S; Appleton CM; Su J; Wahl RL
Radiol Artif Intell; 2024 May; 6(3):e230033. PubMed ID: 38597785
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. 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]
15. Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study.
Dembrower K; Wåhlin E; Liu Y; Salim M; Smith K; Lindholm P; Eklund M; Strand F
Lancet Digit Health; 2020 Sep; 2(9):e468-e474. PubMed ID: 33328114
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Diagnostic Performance of AI for Cancers Registered in A Mammography Screening Program: A Retrospective Analysis.
Kizildag Yirgin I; Koyluoglu YO; Seker ME; Ozkan Gurdal S; Ozaydin AN; Ozcinar B; Cabioğlu N; Ozmen V; Aribal E
Technol Cancer Res Treat; 2022; 21():15330338221075172. PubMed ID: 35060413
[No Abstract] [Full Text] [Related]
18. AI-based prevention of interval cancers in a national mammography screening program.
Byng D; Strauch B; Gnas L; Leibig C; Stephan O; Bunk S; Hecht G
Eur J Radiol; 2022 Jul; 152():110321. PubMed ID: 35512511
[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. 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]
[Next] [New Search]
