149 related articles for article (PubMed ID: 11079854)
1. A Bayesian network for mammography.
Burnside E; Rubin D; Shachter R
Proc AMIA Symp; 2000; ():106-10. PubMed ID: 11079854
[TBL] [Abstract][Full Text] [Related]
2. A probabilistic expert system that provides automated mammographic-histologic correlation: initial experience.
Burnside ES; Rubin DL; Shachter RD; Sohlich RE; Sickles EA
AJR Am J Roentgenol; 2004 Feb; 182(2):481-8. PubMed ID: 14736686
[TBL] [Abstract][Full Text] [Related]
3. Breast imaging reporting and data system standardized mammography lexicon: observer variability in lesion description.
Baker JA; Kornguth PJ; Floyd CE
AJR Am J Roentgenol; 1996 Apr; 166(4):773-8. PubMed ID: 8610547
[TBL] [Abstract][Full Text] [Related]
4. On the interplay of machine learning and background knowledge in image interpretation by Bayesian networks.
Velikova M; Lucas PJ; Samulski M; Karssemeijer N
Artif Intell Med; 2013 Jan; 57(1):73-86. PubMed ID: 23395008
[TBL] [Abstract][Full Text] [Related]
5. External validation of a publicly available computer assisted diagnostic tool for mammographic mass lesions with two high prevalence research datasets.
Benndorf M; Burnside ES; Herda C; Langer M; Kotter E
Med Phys; 2015 Aug; 42(8):4987-96. PubMed ID: 26233224
[TBL] [Abstract][Full Text] [Related]
6. Development of an online, publicly accessible naive Bayesian decision support tool for mammographic mass lesions based on the American College of Radiology (ACR) BI-RADS lexicon.
Benndorf M; Kotter E; Langer M; Herda C; Wu Y; Burnside ES
Eur Radiol; 2015 Jun; 25(6):1768-75. PubMed ID: 25576230
[TBL] [Abstract][Full Text] [Related]
7. Using a Bayesian network to predict the probability and type of breast cancer represented by microcalcifications on mammography.
Burnside ES; Rubin DL; Shachter RD
Stud Health Technol Inform; 2004; 107(Pt 1):13-7. PubMed ID: 15360765
[TBL] [Abstract][Full Text] [Related]
8. Preliminary investigation of a Bayesian network for mammographic diagnosis of breast cancer.
Kahn CE; Roberts LM; Wang K; Jenks D; Haddawy P
Proc Annu Symp Comput Appl Med Care; 1995; ():208-12. PubMed ID: 8563269
[TBL] [Abstract][Full Text] [Related]
9. Probabilistic computer model developed from clinical data in national mammography database format to classify mammographic findings.
Burnside ES; Davis J; Chhatwal J; Alagoz O; Lindstrom MJ; Geller BM; Littenberg B; Shaffer KA; Kahn CE; Page CD
Radiology; 2009 Jun; 251(3):663-72. PubMed ID: 19366902
[TBL] [Abstract][Full Text] [Related]
10. Breast imaging reporting and data system (BI-RADS).
Liberman L; Menell JH
Radiol Clin North Am; 2002 May; 40(3):409-30, v. PubMed ID: 12117184
[TBL] [Abstract][Full Text] [Related]
11. Performance assessment for radiologists interpreting screening mammography.
Woodard DB; Gelfand AE; Barlow WE; Elmore JG
Stat Med; 2007 Mar; 26(7):1532-51. PubMed ID: 16847870
[TBL] [Abstract][Full Text] [Related]
12. Case-based reasoning computer algorithm that uses mammographic findings for breast biopsy decisions.
Floyd CE; Lo JY; Tourassi GD
AJR Am J Roentgenol; 2000 Nov; 175(5):1347-52. PubMed ID: 11044039
[TBL] [Abstract][Full Text] [Related]
13. Objectivity and accuracy of mammogram interpretation using the BI-RADS final assessment categories in 40- to 49-year-old women.
McKay C; Hart CL; Erbacher G
J Am Osteopath Assoc; 2000 Oct; 100(10):615-20. PubMed ID: 11105450
[TBL] [Abstract][Full Text] [Related]
14. A Probabilistic Model to Support Radiologists' Classification Decisions in Mammography Practice.
Zeng J; Gimenez F; Burnside ES; Rubin DL; Shachter R
Med Decis Making; 2019 Apr; 39(3):208-216. PubMed ID: 30819048
[TBL] [Abstract][Full Text] [Related]
15. Mammographic screening and reporting: a need for standardisation. A review.
Akhigbe AO; Igbinedion BO
Niger Postgrad Med J; 2013 Dec; 20(4):346-51. PubMed ID: 24633281
[TBL] [Abstract][Full Text] [Related]
16. Uncertainty modeling for ontology-based mammography annotation with intelligent BI-RADS scoring.
Bulu H; Alpkocak A; Balci P
Comput Biol Med; 2013 May; 43(4):301-11. PubMed ID: 23414780
[TBL] [Abstract][Full Text] [Related]
17. Computer vision and artificial intelligence in mammography.
Vyborny CJ; Giger ML
AJR Am J Roentgenol; 1994 Mar; 162(3):699-708. PubMed ID: 8109525
[TBL] [Abstract][Full Text] [Related]
18. Computerized calculation of breast density: our experience from Arcadia Medical Imaging Center.
Jari I; Ursaru M; Gheorghe L; Naum AG; Negru D
Rev Med Chir Soc Med Nat Iasi; 2014; 118(4):979-85. PubMed ID: 25581957
[TBL] [Abstract][Full Text] [Related]
19. Expert learning system network for diagnosis of breast calcifications.
Patrick EA; Moskowitz M; Mansukhani VT; Gruenstein EI
Invest Radiol; 1991 Jun; 26(6):534-9. PubMed ID: 1860760
[TBL] [Abstract][Full Text] [Related]
20. Applications and literature review of the BI-RADS classification.
Obenauer S; Hermann KP; Grabbe E
Eur Radiol; 2005 May; 15(5):1027-36. PubMed ID: 15856253
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]