-
1
-
-
0027604029
-
Simulation studies of data classification by artificial neural networks: Potential applications in medical imaging and decision making
-
0897-1889.
-
Y. Wu, K. Doi, C. E. Metz, N. Asada, and M. L. Giger, " Simulation studies of data classification by artificial neural networks: Potential applications in medical imaging and decision making.," J. Digit Imaging 0897-1889 6, 117-125 (1993).
-
(1993)
J. Digit Imaging
, vol.6
, pp. 117-125
-
-
Wu, Y.1
Doi, K.2
Metz, C.E.3
Asada, N.4
Giger, M.L.5
-
2
-
-
0030062375
-
Malignant and benign clustered microcalcifications: Automated feature analysis and classification
-
0033-8419.
-
Y. Jiang, " Malignant and benign clustered microcalcifications: Automated feature analysis and classification.," Radiology 0033-8419 198, 671-678 (1996).
-
(1996)
Radiology
, vol.198
, pp. 671-678
-
-
Jiang, Y.1
-
4
-
-
0035437718
-
Ideal observer approximation using Bayesian classification neural networks
-
DOI 10.1109/42.952727, PII S027800620108661X
-
M. A. Kupinski, D. C. Edwards, M. L. Giger, and C. E. Metz, " Ideal observer approximation using Bayesian classification neural networks.," IEEE Trans. Med. Imaging 0278-0062 20, 886-899 (2001). 10.1109/42.952727 (Pubitemid 32992592)
-
(2001)
IEEE Transactions on Medical Imaging
, vol.20
, Issue.9
, pp. 886-899
-
-
Kupinski, M.A.1
Edwards, D.C.2
Giger, M.L.3
Metz, C.E.4
-
5
-
-
0026017007
-
Creating artificial neural networks that generalize
-
0893-6080,. 10.1016/0893-6080(91)90033-2
-
J. Sietsma and R. J. F. Dow, " Creating artificial neural networks that generalize.," Neural Networks 0893-6080 4, 67-79 (1991). 10.1016/0893-6080(91)90033-2
-
(1991)
Neural Networks
, vol.4
, pp. 67-79
-
-
Sietsma, J.1
Dow, R.J.F.2
-
6
-
-
0001942829
-
Neural networks and the bias/variance dilemma
-
0899-7667,. 10.1162/neco.1992.4.1.1
-
S. Geman, E. Bienenstock, and R. Doursat, " Neural networks and the bias/variance dilemma.," Neural Comput. 0899-7667 4, 1-58 (1992). 10.1162/neco.1992.4.1.1
-
(1992)
Neural Comput.
, vol.4
, pp. 1-58
-
-
Geman, S.1
Bienenstock, E.2
Doursat, R.3
-
7
-
-
0003684449
-
-
(Springer, New York).
-
T. Hastie, R. Tibshirani, and J. H. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Springer, New York, 2001).
-
(2001)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
-
-
Hastie, T.1
Tibshirani, R.2
Friedman, J.H.3
-
10
-
-
85027229772
-
-
Neural Network FAQ. Retrieved September 9, (website:).
-
W. S. Sarle, Neural Network FAQ. Retrieved September 9, 2008 (website: ftp://ftp.sas.com/pub/neural/FAQ.html).
-
(2008)
-
-
Sarle, W.S.1
-
11
-
-
2342565172
-
The effects of adding noise during backpropagation training on a generalization performance
-
0899-7667,. 10.1162/neco.1996.8.3.643
-
G. Z. An, " The effects of adding noise during backpropagation training on a generalization performance.," Neural Comput. 0899-7667 8, 643-674 (1996). 10.1162/neco.1996.8.3.643
-
(1996)
Neural Comput.
, vol.8
, pp. 643-674
-
-
An, G.Z.1
-
12
-
-
0001740650
-
Training with noise is equivalent to Tikhonov regularization
-
0899-7667,. 10.1162/neco.1995.7.1.108
-
C. M. Bishop, " Training with noise is equivalent to Tikhonov regularization.," Neural Comput. 0899-7667 7, 108-116 (1995). 10.1162/neco.1995.7.1.108
-
(1995)
Neural Comput.
, vol.7
, pp. 108-116
-
-
Bishop, C.M.1
-
13
-
-
0013230715
-
Noise injection: Theoretical prospects
-
0899-7667,. 10.1162/neco.1997.9.5.1093
-
Y. Grandvalet, S. Canu, and S. Boucheron, " Noise injection: theoretical prospects.," Neural Comput. 0899-7667 9, 1093-1108 (1997). 10.1162/neco.1997.9.5.1093
-
(1997)
Neural Comput.
, vol.9
, pp. 1093-1108
-
-
Grandvalet, Y.1
Canu, S.2
Boucheron, S.3
-
14
-
-
0026624071
-
Using additive noise in back-propagation training
-
1045-9227,. 10.1109/72.105415
-
L. Holmström and P. Koistinen, " Using additive noise in back-propagation training.," IEEE Trans. Neural Netw. 1045-9227 3, 24-38 (1992). 10.1109/72.105415
-
(1992)
IEEE Trans. Neural Netw.
, vol.3
, pp. 24-38
-
-
Holmström, L.1
Koistinen, P.2
-
15
-
-
0026858102
-
Noise injection into inputs in backpropagation learning
-
0018-9472,. 10.1109/21.155944
-
K. Matsuoka, " Noise injection into inputs in backpropagation learning.," IEEE Trans. Syst. Man Cybern. 0018-9472 22, 436-440 (1992). 10.1109/21.155944
-
(1992)
IEEE Trans. Syst. Man Cybern.
, vol.22
, pp. 436-440
-
-
Matsuoka, K.1
-
16
-
-
70349687972
-
-
in, edited by A. J. C. Sharkey (Springer, New York),.
-
Y. Raviv and N. Intrator, in Combining Artificial Neural Nets: Ensemble and Modular Multi-net Systems, edited by, A. J. C. Sharkey, (Springer, New York, 1999), p. 298.
-
(1999)
Combining Artificial Neural Nets: Ensemble and Modular Multi-net Systems
, pp. 298
-
-
Raviv, Y.1
Intrator, N.2
-
17
-
-
0033317598
-
Bayesian approach to neural-network modeling with input uncertainty
-
DOI 10.1109/72.809073
-
W. A. Wright, " Bayesian approach to neural-network modeling with input uncertainty.," IEEE Trans. Neural Netw. 1045-9227 10, 1261-1270 (1999). 10.1109/72.809073 (Pubitemid 30536598)
-
(1999)
IEEE Transactions on Neural Networks
, vol.10
, Issue.6
, pp. 1261-1270
-
-
Wright, W.A.1
-
18
-
-
0034244839
-
Neural network modelling with input uncertainty: Theory and application
-
10.1023/A:1008111920791
-
W. A. Wright, G. Ramage, D. Cornford, and I. Nabney, " Neural network modelling with input uncertainty: Theory and application.," J. VLSI Sig. Proc. Syst. 26, 169-188 (2000). 10.1023/A:1008111920791
-
(2000)
J. VLSI Sig. Proc. Syst.
, vol.26
, pp. 169-188
-
-
Wright, W.A.1
Ramage, G.2
Cornford, D.3
Nabney, I.4
-
19
-
-
33645204782
-
Comparison of two methods of adding jitter to artificial neural network training
-
(Elsevier, Chicago)
-
R. M. Zur, Y. Jiang, and C. E. Metz, " Comparison of two methods of adding jitter to artificial neural network training.," Proceedings of CARS (Elsevier, Chicago, 2004), pp. 886-889.
-
(2004)
Proceedings of CARS
, pp. 886-889
-
-
Zur, R.M.1
Jiang, Y.2
Metz, C.E.3
-
21
-
-
0022470978
-
ROC methodology in radiologic imaging
-
0020-9996,. 10.1097/00004424-198609000-00009
-
C. E. Metz, " ROC methodology in radiologic imaging.," Invest. Radiol. 0020-9996 21, 720-733 (1986). 10.1097/00004424-198609000-00009
-
(1986)
Invest. Radiol.
, vol.21
, pp. 720-733
-
-
Metz, C.E.1
-
22
-
-
34250162528
-
Assessment of Medical Imaging Systems and Computer Aids: A Tutorial Review
-
DOI 10.1016/j.acra.2007.03.001, PII S1076633207001377
-
R. F. Wagner, C. E. Metz, and G. Campbell, " Assessment of medical imaging systems and computer aids: A tutorial review.," Acad. Radiol. 1076-6332 14, 723-748 (2007). 10.1016/j.acra.2007.03.001 (Pubitemid 46898203)
-
(2007)
Academic Radiology
, vol.14
, Issue.6
, pp. 723-748
-
-
Wagner, R.F.1
Metz, C.E.2
Campbell, G.3
-
24
-
-
0002822137
-
'Proper binormal ROC curves: Theory and maximum-likelihood estimation
-
0022-2496,. 10.1006/jmps.1998.1218
-
C. E. Metz and X. Pan, " 'Proper binormal ROC curves: Theory and maximum-likelihood estimation.," J. Math. Psychol. 0022-2496 43, 1-33 (1999). 10.1006/jmps.1998.1218
-
(1999)
J. Math. Psychol.
, vol.43
, pp. 1-33
-
-
Metz, C.E.1
Pan, X.2
-
25
-
-
49049083896
-
Breast US computer-aided diagnosis workstation: Performance with a large clinical diagnostic population
-
0033-8419,. 10.1148/radiol.2482071778
-
K. Drukker, N. P. Gruszauskas, C. A. Sennett, and M. L. Giger, " Breast US computer-aided diagnosis workstation: Performance with a large clinical diagnostic population.," Radiology 0033-8419 248, 392-397 (2008). 10.1148/radiol.2482071778
-
(2008)
Radiology
, vol.248
, pp. 392-397
-
-
Drukker, K.1
Gruszauskas, N.P.2
Sennett, C.A.3
Giger, M.L.4
-
27
-
-
0042025303
-
Uncertainty in the output of artificial neural networks
-
0278-0062,. 10.1109/TMI.2003.815061
-
Y. Jiang, " Uncertainty in the output of artificial neural networks.," IEEE Trans. Med. Imaging 0278-0062 22, 913-921 (2003). 10.1109/TMI.2003.815061
-
(2003)
IEEE Trans. Med. Imaging
, vol.22
, pp. 913-921
-
-
Jiang, Y.1
-
28
-
-
0035312886
-
Bayesian approach for neural networks - Review and case studies
-
DOI 10.1016/S0893-6080(00)00098-8, PII S0893608000000988
-
J. Lampinen and A. Vehtari, " Bayesian approach for neural networks-review and case studies.," Neural Networks 0893-6080 14, 257-274 (2001). 10.1016/S0893-6080(00)00098-8 (Pubitemid 32288857)
-
(2001)
Neural Networks
, vol.14
, Issue.3
, pp. 257-274
-
-
Lampinen, J.1
Vehtari, A.2
-
29
-
-
51749097121
-
Classifier performance estimation under the constraint of a finite sample size: Resampling schemes applied to neural network classifiers
-
(IEEE, Orlando)
-
B. Sahiner, H. P. Chan, and L. Hadjiiski, " Classifier performance estimation under the constraint of a finite sample size: resampling schemes applied to neural network classifiers.," Proceedings of IJCNN (IEEE, Orlando, 2007), pp. 1762-1766.
-
(2007)
Proceedings of IJCNN
, pp. 1762-1766
-
-
Sahiner, B.1
Chan, H.P.2
Hadjiiski, L.3
-
30
-
-
27644512013
-
Comparison of non-parametric methods for assessing classifier performance in terms of ROC parameters
-
(IEEE, Washington)
-
W. A. Yousef, R. F. Wagner, and M. H. Loew, " Comparison of non-parametric methods for assessing classifier performance in terms of ROC parameters.," Proceedings of the 33rd AIPR Workshop (IEEE, Washington, 2004), pp. 190-195.
-
(2004)
Proceedings of the 33rd AIPR Workshop
, pp. 190-195
-
-
Yousef, W.A.1
Wagner, R.F.2
Loew, M.H.3
-
32
-
-
0033461791
-
Classifier design for computer-aided diagnosis: Effects of finite sample size on the mean performance of classical and neural network classifiers
-
DOI 10.1118/1.598805
-
H. P. Chan, B. Sahiner, R. F. Wagner, and N. Petrick, " Classifier design for computer-aided diagnosis: Effects of finite sample size on the mean performance of classical and neural network classifiers.," Med. Phys. 0094-2405 26, 2654-2668 (1999). 10.1118/1.598805 (Pubitemid 30007711)
-
(1999)
Medical Physics
, vol.26
, Issue.12
, pp. 2654-2668
-
-
Chan, H.-P.1
Sahiner, B.2
Wagner, R.F.3
Petrick, N.4
-
33
-
-
73949105476
-
On experimental design and data analysis in receiver operating characteristic (ROC) studies: Lessons learned from papers published in Radiology from 1997 to 2006
-
0033-8419 (in press).
-
J. Shiraishi, L. Pesce, C. E. Metz, and K. Doi, " On experimental design and data analysis in receiver operating characteristic (ROC) studies: Lessons learned from papers published in Radiology from 1997 to 2006.," Radiology 0033-8419 (in press).
-
Radiology
-
-
Shiraishi, J.1
Pesce, L.2
Metz, C.E.3
Doi, K.4
|