651 related articles for article (PubMed ID: 31063083)
1. A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction.
Yala A; Lehman C; Schuster T; Portnoi T; Barzilay R
Radiology; 2019 Jul; 292(1):60-66. PubMed ID: 31063083
[TBL] [Abstract][Full Text] [Related]
2. Comparison of a Deep Learning Risk Score and Standard Mammographic Density Score for Breast Cancer Risk Prediction.
Dembrower K; Liu Y; Azizpour H; Eklund M; Smith K; Lindholm P; Strand F
Radiology; 2020 Feb; 294(2):265-272. PubMed ID: 31845842
[TBL] [Abstract][Full Text] [Related]
3. Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms.
Akselrod-Ballin A; Chorev M; Shoshan Y; Spiro A; Hazan A; Melamed R; Barkan E; Herzel E; Naor S; Karavani E; Koren G; Goldschmidt Y; Shalev V; Rosen-Zvi M; Guindy M
Radiology; 2019 Aug; 292(2):331-342. PubMed ID: 31210611
[TBL] [Abstract][Full Text] [Related]
4. A Deep Learning Model to Triage Screening Mammograms: A Simulation Study.
Yala A; Schuster T; Miles R; Barzilay R; Lehman C
Radiology; 2019 Oct; 293(1):38-46. PubMed ID: 31385754
[TBL] [Abstract][Full Text] [Related]
5. Mammographic Breast Density Assessment Using Deep Learning: Clinical Implementation.
Lehman CD; Yala A; Schuster T; Dontchos B; Bahl M; Swanson K; Barzilay R
Radiology; 2019 Jan; 290(1):52-58. PubMed ID: 30325282
[TBL] [Abstract][Full Text] [Related]
6. Deep Learning Predicts Interval and Screening-detected Cancer from Screening Mammograms: A Case-Case-Control Study in 6369 Women.
Zhu X; Wolfgruber TK; Leong L; Jensen M; Scott C; Winham S; Sadowski P; Vachon C; Kerlikowske K; Shepherd JA
Radiology; 2021 Dec; 301(3):550-558. PubMed ID: 34491131
[TBL] [Abstract][Full Text] [Related]
7. Deep Learning vs Traditional Breast Cancer Risk Models to Support Risk-Based Mammography Screening.
Lehman CD; Mercaldo S; Lamb LR; King TA; Ellisen LW; Specht M; Tamimi RM
J Natl Cancer Inst; 2022 Oct; 114(10):1355-1363. PubMed ID: 35876790
[TBL] [Abstract][Full Text] [Related]
8. Deep learning networks find unique mammographic differences in previous negative mammograms between interval and screen-detected cancers: a case-case study.
Hinton B; Ma L; Mahmoudzadeh AP; Malkov S; Fan B; Greenwood H; Joe B; Lee V; Kerlikowske K; Shepherd J
Cancer Imaging; 2019 Jun; 19(1):41. PubMed ID: 31228956
[TBL] [Abstract][Full Text] [Related]
9. Long-term Accuracy of Breast Cancer Risk Assessment Combining Classic Risk Factors and Breast Density.
Brentnall AR; Cuzick J; Buist DSM; Bowles EJA
JAMA Oncol; 2018 Sep; 4(9):e180174. PubMed ID: 29621362
[TBL] [Abstract][Full Text] [Related]
10. Computer-aided assessment of breast density: comparison of supervised deep learning and feature-based statistical learning.
Li S; Wei J; Chan HP; Helvie MA; Roubidoux MA; Lu Y; Zhou C; Hadjiiski LM; Samala RK
Phys Med Biol; 2018 Jan; 63(2):025005. PubMed ID: 29210358
[TBL] [Abstract][Full Text] [Related]
11. A deep learning model integrating mammography and clinical factors facilitates the malignancy prediction of BI-RADS 4 microcalcifications in breast cancer screening.
Liu H; Chen Y; Zhang Y; Wang L; Luo R; Wu H; Wu C; Zhang H; Tan W; Yin H; Wang D
Eur Radiol; 2021 Aug; 31(8):5902-5912. PubMed ID: 33496829
[TBL] [Abstract][Full Text] [Related]
12. Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning.
Zhou LQ; Wu XL; Huang SY; Wu GG; Ye HR; Wei Q; Bao LY; Deng YB; Li XR; Cui XW; Dietrich CF
Radiology; 2020 Jan; 294(1):19-28. PubMed ID: 31746687
[TBL] [Abstract][Full Text] [Related]
13. Effect of Digital Mammography for Breast Cancer Screening: A Comparative Study of More than 8 Million Korean Women.
Hong S; Song SY; Park B; Suh M; Choi KS; Jung SE; Kim MJ; Lee EH; Lee CW; Jun JK
Radiology; 2020 Feb; 294(2):247-255. PubMed ID: 31793847
[TBL] [Abstract][Full Text] [Related]
14. Comparison of the Diagnostic Accuracy of Mammogram-based Deep Learning and Traditional Breast Cancer Risk Models in Patients Who Underwent Supplemental Screening with MRI.
Lamb LR; Mercaldo SF; Ghaderi K; Carney A; Lehman CD
Radiology; 2023 Sep; 308(3):e223077. PubMed ID: 37724967
[TBL] [Abstract][Full Text] [Related]
15. Breast density prediction from low and standard dose mammograms using deep learning: effect of image resolution and model training approach on prediction quality.
Squires S; Harkness EF; Mackenzie A; Evans DG; Howell SJ; Astley SM
Biomed Phys Eng Express; 2024 May; 10(4):. PubMed ID: 38701765
[No Abstract] [Full Text] [Related]
16. 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]
17. Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction.
Gastounioti A; Kasi CD; Scott CG; Brandt KR; Jensen MR; Hruska CB; Wu FF; Norman AD; Conant EF; Winham SJ; Kerlikowske K; Kontos D; Vachon CM
Radiology; 2020 Jul; 296(1):24-31. PubMed ID: 32396041
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Impact of prior mammograms on combined reading of digital mammography and digital breast tomosynthesis.
Kim WH; Chang JM; Koo HR; Seo M; Bae MS; Lee J; Moon WK
Acta Radiol; 2017 Feb; 58(2):148-155. PubMed ID: 27178032
[TBL] [Abstract][Full Text] [Related]
20. Deep Learning Model to Assess Cancer Risk on the Basis of a Breast MR Image Alone.
Portnoi T; Yala A; Schuster T; Barzilay R; Dontchos B; Lamb L; Lehman C
AJR Am J Roentgenol; 2019 Jul; 213(1):227-233. PubMed ID: 30933651
[No Abstract] [Full Text] [Related]
[Next] [New Search]
