262 related articles for article (PubMed ID: 35704111)
1. 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]
2. 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]
3. 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]
4. 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]
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. 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]
7. Artificial Intelligence Evaluation of 122 969 Mammography Examinations from a Population-based Screening Program.
Larsen M; Aglen CF; Lee CI; Hoff SR; Lund-Hanssen H; Lång K; Nygård JF; Ursin G; Hofvind S
Radiology; 2022 Jun; 303(3):502-511. PubMed ID: 35348377
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. 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]
10. 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]
11. 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]
12. 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]
13. Screen-detected and interval breast cancer after concordant and discordant interpretations in a population based screening program using independent double reading.
Martiniussen MA; Sagstad S; Larsen M; Larsen ASF; Hovda T; Lee CI; Hofvind S
Eur Radiol; 2022 Sep; 32(9):5974-5985. PubMed ID: 35364710
[TBL] [Abstract][Full Text] [Related]
14. Protocol for evaluating the fitness for purpose of an artificial intelligence product for radiology reporting in the BreastScreen New South Wales breast cancer screening programme.
Warner-Smith M; Ren K; Mistry C; Walton R; Roder D; Bhola N; McGill S; O'Brien TA
BMJ Open; 2024 May; 14(5):e082350. PubMed ID: 38806433
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. 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]
17. 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]
18. AI Risk Score on Screening Mammograms Preceding Breast Cancer Diagnosis.
Larsen M; Olstad CF; Koch HW; Martiniussen MA; Hoff SR; Lund-Hanssen H; Solli HS; Mikalsen KØ; Auensen S; Nygård J; Lång K; Chen Y; Hofvind S
Radiology; 2023 Oct; 309(1):e230989. PubMed ID: 37847135
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. 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]
[Next] [New Search]
