BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

151 related articles for article (PubMed ID: 37368543)

  • 1. Deep Learning Approaches with Digital Mammography for Evaluating Breast Cancer Risk, a Narrative Review.
    Siddique M; Liu M; Duong P; Jambawalikar S; Ha R
    Tomography; 2023 Jun; 9(3):1110-1119. PubMed ID: 37368543
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep convolutional neural networks for mammography: advances, challenges and applications.
    Abdelhafiz D; Yang C; Ammar R; Nabavi S
    BMC Bioinformatics; 2019 Jun; 20(Suppl 11):281. PubMed ID: 31167642
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Artificial intelligence in breast imaging.
    Le EPV; Wang Y; Huang Y; Hickman S; Gilbert FJ
    Clin Radiol; 2019 May; 74(5):357-366. PubMed ID: 30898381
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Artificial Intelligence for Breast Cancer Risk Assessment.
    Lowry KP; Zuiderveld CC
    Radiol Clin North Am; 2024 Jul; 62(4):619-625. PubMed ID: 38777538
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Spatiotemporal Mammography-based Deep Learning Model for Improved Breast Cancer Risk Prediction.
    Melek A; Fakhry S; Basha T
    Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38170653
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A Review of Artificial Intelligence in Breast Imaging.
    Al-Karawi D; Al-Zaidi S; Helael KA; Obeidat N; Mouhsen AM; Ajam T; Alshalabi BA; Salman M; Ahmed MH
    Tomography; 2024 May; 10(5):705-726. PubMed ID: 38787015
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Breast cancer risk prediction using machine learning: a systematic review.
    Hussain S; Ali M; Naseem U; Nezhadmoghadam F; Jatoi MA; Gulliver TA; Tamez-Peña JG
    Front Oncol; 2024; 14():1343627. PubMed ID: 38571502
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Clinical Artificial Intelligence Applications: Breast Imaging.
    Hu Q; Giger ML
    Radiol Clin North Am; 2021 Nov; 59(6):1027-1043. PubMed ID: 34689871
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Artificial intelligence-based classification of breast lesion from contrast enhanced mammography: a multicenter study.
    Zhang H; Lin F; Zheng T; Gao J; Wang Z; Zhang K; Zhang X; Xu C; Zhao F; Xie H; Li Q; Cao K; Gu Y; Mao N
    Int J Surg; 2024 May; 110(5):2593-2603. PubMed ID: 38748500
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Hardware deployment of deep learning model for classification of breast carcinoma from digital mammogram images.
    R K; H HM; S M; Venkatraman R; Patil S
    Med Biol Eng Comput; 2023 Nov; 61(11):2843-2857. PubMed ID: 37495885
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Artificial intelligence in breast imaging: potentials and challenges.
    Li JW; Sheng DL; Chen JG; You C; Liu S; Xu HX; Chang C
    Phys Med Biol; 2023 Nov; 68(23):. PubMed ID: 37722385
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Breast Cancer Detection and Diagnosis Using Mammographic Data: Systematic Review.
    Gardezi SJS; Elazab A; Lei B; Wang T
    J Med Internet Res; 2019 Jul; 21(7):e14464. PubMed ID: 31350843
    [TBL] [Abstract][Full Text] [Related]  

  • 13. AI-enhanced breast imaging: Where are we and where are we heading?
    Bitencourt A; Daimiel Naranjo I; Lo Gullo R; Rossi Saccarelli C; Pinker K
    Eur J Radiol; 2021 Sep; 142():109882. PubMed ID: 34392105
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Artificial Intelligence in plastic surgery: What is it? Where are we now? What is on the horizon?
    Murphy DC; Saleh DB
    Ann R Coll Surg Engl; 2020 Oct; 102(8):577-580. PubMed ID: 32777930
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Recent advancements in machine learning and deep learning-based breast cancer detection using mammograms.
    Sahu A; Das PK; Meher S
    Phys Med; 2023 Oct; 114():103138. PubMed ID: 37914431
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Deep learning for computer-aided abnormalities classification in digital mammogram: A data-centric perspective.
    Nalla V; Pouriyeh S; Parizi RM; Trivedi H; Sheng QZ; Hwang I; Seyyed-Kalantari L; Woo M
    Curr Probl Diagn Radiol; 2024; 53(3):346-352. PubMed ID: 38302303
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Artificial intelligence and convolution neural networks assessing mammographic images: a narrative literature review.
    Wong DJ; Gandomkar Z; Wu WJ; Zhang G; Gao W; He X; Wang Y; Reed W
    J Med Radiat Sci; 2020 Jun; 67(2):134-142. PubMed ID: 32134206
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Recent advancements in artificial intelligence for breast cancer: Image augmentation, segmentation, diagnosis, and prognosis approaches.
    Zhang J; Wu J; Zhou XS; Shi F; Shen D
    Semin Cancer Biol; 2023 Nov; 96():11-25. PubMed ID: 37704183
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Machine learning and new insights for breast cancer diagnosis.
    Guo Y; Zhang H; Yuan L; Chen W; Zhao H; Yu QQ; Shi W
    J Int Med Res; 2024 Apr; 52(4):3000605241237867. PubMed ID: 38663911
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Advances in breast cancer risk modeling: integrating clinics, imaging, pathology and artificial intelligence for personalized risk assessment.
    Pesapane F; Battaglia O; Pellegrino G; Mangione E; Petitto S; Fiol Manna ED; Cazzaniga L; Nicosia L; Lazzeroni M; Corso G; Fusco N; Cassano E
    Future Oncol; 2023 Dec; 19(38):2547-2564. PubMed ID: 38084492
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.