BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

166 related articles for article (PubMed ID: 38326868)

  • 1. Are better AI algorithms for breast cancer detection also better at predicting risk? A paired case-control study.
    Santeramo R; Damiani C; Wei J; Montana G; Brentnall AR
    Breast Cancer Res; 2024 Feb; 26(1):25. PubMed ID: 38326868
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Evaluation of an AI Model to Assess Future Breast Cancer Risk.
    Damiani C; Kalliatakis G; Sreenivas M; Al-Attar M; Rose J; Pudney C; Lane EF; Cuzick J; Montana G; Brentnall AR
    Radiology; 2023 Jun; 307(5):e222679. PubMed ID: 37310244
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Screening mammography performance according to breast density: a comparison between radiologists versus standalone intelligence detection.
    Kwon MR; Chang Y; Ham SY; Cho Y; Kim EY; Kang J; Park EK; Kim KH; Kim M; Kim TS; Lee H; Kwon R; Lim GY; Choi HR; Choi J; Kook SH; Ryu S
    Breast Cancer Res; 2024 Apr; 26(1):68. PubMed ID: 38649889
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. 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]  

  • 7. AsymMirai: Interpretable Mammography-based Deep Learning Model for 1-5-year Breast Cancer Risk Prediction.
    Donnelly J; Moffett L; Barnett AJ; Trivedi H; Schwartz F; Lo J; Rudin C
    Radiology; 2024 Mar; 310(3):e232780. PubMed ID: 38501952
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Comparison of Mammography AI Algorithms with a Clinical Risk Model for 5-year Breast Cancer Risk Prediction: An Observational Study.
    Arasu VA; Habel LA; Achacoso NS; Buist DSM; Cord JB; Esserman LJ; Hylton NM; Glymour MM; Kornak J; Kushi LH; Lewis DA; Liu VX; Lydon CM; Miglioretti DL; Navarro DA; Pu A; Shen L; Sieh W; Yoon HC; Lee C
    Radiology; 2023 Jun; 307(5):e222733. PubMed ID: 37278627
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep-LIBRA: An artificial-intelligence method for robust quantification of breast density with independent validation in breast cancer risk assessment.
    Haji Maghsoudi O; Gastounioti A; Scott C; Pantalone L; Wu FF; Cohen EA; Winham S; Conant EF; Vachon C; Kontos D
    Med Image Anal; 2021 Oct; 73():102138. PubMed ID: 34274690
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. 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]  

  • 12. Impact of Artificial Intelligence System and Volumetric Density on Risk Prediction of Interval, Screen-Detected, and Advanced Breast Cancer.
    Vachon CM; Scott CG; Norman AD; Khanani SA; Jensen MR; Hruska CB; Brandt KR; Winham SJ; Kerlikowske K
    J Clin Oncol; 2023 Jun; 41(17):3172-3183. PubMed ID: 37104728
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. External Validation of an Ensemble Model for Automated Mammography Interpretation by Artificial Intelligence.
    Hsu W; Hippe DS; Nakhaei N; Wang PC; Zhu B; Siu N; Ahsen ME; Lotter W; Sorensen AG; Naeim A; Buist DSM; Schaffter T; Guinney J; Elmore JG; Lee CI
    JAMA Netw Open; 2022 Nov; 5(11):e2242343. PubMed ID: 36409497
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Interval Cancer Detection Using a Neural Network and Breast Density in Women with Negative Screening Mammograms.
    Wanders AJT; Mees W; Bun PAM; Janssen N; Rodríguez-Ruiz A; Dalmış MU; Karssemeijer N; van Gils CH; Sechopoulos I; Mann RM; van Rooden CJ
    Radiology; 2022 May; 303(2):269-275. PubMed ID: 35133194
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. External Evaluation of a Mammography-based Deep Learning Model for Predicting Breast Cancer in an Ethnically Diverse Population.
    Omoleye OJ; Woodard AE; Howard FM; Zhao F; Yoshimatsu TF; Zheng Y; Pearson AT; Levental M; Aribisala BS; Kulkarni K; Karczmar GS; Olopade OI; Abe H; Huo D
    Radiol Artif Intell; 2023 Nov; 5(6):e220299. PubMed ID: 38074785
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Multi-Institutional Validation of a Mammography-Based Breast Cancer Risk Model.
    Yala A; Mikhael PG; Strand F; Lin G; Satuluru S; Kim T; Banerjee I; Gichoya J; Trivedi H; Lehman CD; Hughes K; Sheedy DJ; Matthis LM; Karunakaran B; Hegarty KE; Sabino S; Silva TB; Evangelista MC; Caron RF; Souza B; Mauad EC; Patalon T; Handelman-Gotlib S; Guindy M; Barzilay R
    J Clin Oncol; 2022 Jun; 40(16):1732-1740. PubMed ID: 34767469
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Deep learning modeling using normal mammograms for predicting breast cancer risk.
    Arefan D; Mohamed AA; Berg WA; Zuley ML; Sumkin JH; Wu S
    Med Phys; 2020 Jan; 47(1):110-118. PubMed ID: 31667873
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.