177 related articles for article (PubMed ID: 16550707)
1. A tutorial on the use of ROC analysis for computer-aided diagnostic systems.
Scheipers U; Perrey C; Siebers S; Hansen C; Ermert H
Ultrason Imaging; 2005 Jul; 27(3):181-98. PubMed ID: 16550707
[TBL] [Abstract][Full Text] [Related]
2. Receiver operating characteristic analysis for intelligent medical systems--a new approach for finding confidence intervals.
Tilbury JB; Van Eetvelt PW; Garibaldi JM; Curnow JS; Ifeachor EC
IEEE Trans Biomed Eng; 2000 Jul; 47(7):952-63. PubMed ID: 10916267
[TBL] [Abstract][Full Text] [Related]
3. Automated method for improving system performance of computer-aided diagnosis in breast ultrasound.
Drukker K; Sennett CA; Giger ML
IEEE Trans Med Imaging; 2009 Jan; 28(1):122-8. PubMed ID: 19116194
[TBL] [Abstract][Full Text] [Related]
4. [Application of a computer-aided detection (CAD) system to digitalized mammograms for identifying microcalcifications].
Bazzocchi M; Facecchia I; Zuiani C; Londero V; Smania S; Bottigli U; Delogu P
Radiol Med; 2001 May; 101(5):334-40. PubMed ID: 11438784
[TBL] [Abstract][Full Text] [Related]
5. Comparison of independent double readings and computer-aided diagnosis (CAD) for the diagnosis of breast calcifications.
Jiang Y; Nishikawa RM; Schmidt RA; Metz CE
Acad Radiol; 2006 Jan; 13(1):84-94. PubMed ID: 16399036
[TBL] [Abstract][Full Text] [Related]
6. A program for computing the prediction probability and the related receiver operating characteristic graph.
Jordan D; Steiner M; Kochs EF; Schneider G
Anesth Analg; 2010 Dec; 111(6):1416-21. PubMed ID: 21059744
[TBL] [Abstract][Full Text] [Related]
7. Computer-aided US diagnosis of breast lesions by using cell-based contour grouping.
Cheng JZ; Chou YH; Huang CS; Chang YC; Tiu CM; Chen KW; Chen CM
Radiology; 2010 Jun; 255(3):746-54. PubMed ID: 20501714
[TBL] [Abstract][Full Text] [Related]
8. Computer-aided classification of BI-RADS category 3 breast lesions.
Buchbinder SS; Leichter IS; Lederman RB; Novak B; Bamberger PN; Sklair-Levy M; Yarmish G; Fields SI
Radiology; 2004 Mar; 230(3):820-3. PubMed ID: 14739315
[TBL] [Abstract][Full Text] [Related]
9. Exploring medical diagnostic performance using interactive, multi-parameter sourced receiver operating characteristic scatter plots.
Moore HE; Andlauer O; Simon N; Mignot E
Comput Biol Med; 2014 Apr; 47():120-9. PubMed ID: 24561350
[TBL] [Abstract][Full Text] [Related]
10. A Metric for Reducing False Positives in the Computer-Aided Detection of Breast Cancer from Dynamic Contrast-Enhanced Magnetic Resonance Imaging Based Screening Examinations of High-Risk Women.
Levman JE; Gallego-Ortiz C; Warner E; Causer P; Martel AL
J Digit Imaging; 2016 Feb; 29(1):126-33. PubMed ID: 26293705
[TBL] [Abstract][Full Text] [Related]
11. Evaluation of partial classification algorithms using ROC curves.
Tusch G
Medinfo; 1995; 8 Pt 2():904-8. PubMed ID: 8591580
[TBL] [Abstract][Full Text] [Related]
12. Effect of correlation on combining diagnostic information from two images of the same patient.
Liu B; Metz CE; Jiang Y
Med Phys; 2005 Nov; 32(11):3329-38. PubMed ID: 16372412
[TBL] [Abstract][Full Text] [Related]
13. Classification of breast mass lesions using model-based analysis of the characteristic kinetic curve derived from fuzzy c-means clustering.
Chang YC; Huang YH; Huang CS; Chang PK; Chen JH; Chang RF
Magn Reson Imaging; 2012 Apr; 30(3):312-22. PubMed ID: 22245697
[TBL] [Abstract][Full Text] [Related]
14. Computer-aided characterization of mammographic masses: accuracy of mass segmentation and its effects on characterization.
Sahiner B; Petrick N; Chan HP; Hadjiiski LM; Paramagul C; Helvie MA; Gurcan MN
IEEE Trans Med Imaging; 2001 Dec; 20(12):1275-84. PubMed ID: 11811827
[TBL] [Abstract][Full Text] [Related]
15. Comparative analysis of logistic regression and artificial neural network for computer-aided diagnosis of breast masses.
Song JH; Venkatesh SS; Conant EA; Arger PH; Sehgal CM
Acad Radiol; 2005 Apr; 12(4):487-95. PubMed ID: 15831423
[TBL] [Abstract][Full Text] [Related]
16. Computer aided classification of masses in ultrasonic mammography.
Dumane VA; Shankar PM; Piccoli CW; Reid JM; Forsberg F; Goldberg BB
Med Phys; 2002 Sep; 29(9):1968-73. PubMed ID: 12349916
[TBL] [Abstract][Full Text] [Related]
17. Characterization of spatiotemporal changes for the classification of dynamic contrast-enhanced magnetic-resonance breast lesions.
Milenković J; Hertl K; Košir A; Zibert J; Tasič JF
Artif Intell Med; 2013 Jun; 58(2):101-14. PubMed ID: 23548472
[TBL] [Abstract][Full Text] [Related]
18. Application of Computer-Aided Diagnosis to the Sonographic Evaluation of Cervical Lymph Nodes.
Zhang J; Wang Y; Yu B; Shi X; Zhang Y
Ultrason Imaging; 2016 Mar; 38(2):159-71. PubMed ID: 26025577
[TBL] [Abstract][Full Text] [Related]
19. Classification of breast lesions with multimodality computer-aided diagnosis: observer study results on an independent clinical data set.
Horsch K; Giger ML; Vyborny CJ; Lan L; Mendelson EB; Hendrick RE
Radiology; 2006 Aug; 240(2):357-68. PubMed ID: 16864666
[TBL] [Abstract][Full Text] [Related]
20. An ROC comparison of four methods of combining information from multiple images of the same patient.
Liu B; Metz CE; Jiang Y
Med Phys; 2004 Sep; 31(9):2552-63. PubMed ID: 15487738
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]