-
1
-
-
0041402684
-
Survival Analysis Part I: Basic concepts and first analyses
-
DOI 10.1038/sj.bjc.6601118
-
T. G. Clark, M. J. Bradburn, S. B. Love, and D. G. Altman, "Survival analysis part i: Basic concepts and first analyses," British Journal of Cancer, vol. 89, no. 2, pp. 232-238, 2003. (Pubitemid 36976306)
-
(2003)
British Journal of Cancer
, vol.89
, Issue.2
, pp. 232-238
-
-
Clark, T.G.1
Bradburn, M.J.2
Love, S.B.3
Altman, D.G.4
-
3
-
-
0031921607
-
Feed forward neural networks for the analysis of censored survival data: A partial logistic regression approach
-
DOI 10.1002/(SICI)1097-0258(19980530)17:10<1169::AID-SIM796>3.0. CO;2-D
-
E. Biganzoli, P. Boracchi, L. Mariani, and E. Marubini, "Feed forward neural networks for the analysis of censored survival data: a partial logistic regression approach," Statistics in Medicine, vol. 17, no. 10, pp. 1169-1186, 1998. (Pubitemid 28221032)
-
(1998)
Statistics in Medicine
, vol.17
, Issue.10
, pp. 1169-1186
-
-
Biganzoli, E.1
Boracchi, P.2
Mariani, L.3
Marubini, E.4
-
4
-
-
33746901239
-
The use of artificial neural networks in decision support in cancer: A systematic review
-
DOI 10.1016/j.neunet.2005.10.007, PII S0893608005002844
-
P. J. G. Lisboa and A. F. G. Taktak, "The use of artificial neural networks in decision support in cancer: A systematic review," Neural Networks, vol. 19, no. 4, pp. 408-415, 2006. (Pubitemid 44183627)
-
(2006)
Neural Networks
, vol.19
, Issue.4
, pp. 408-415
-
-
Lisboa, P.J.1
Taktak, A.F.G.2
-
5
-
-
0043126911
-
Logistic regression and artificial neural network classification models: A methodology review
-
DOI 10.1016/S1532-0464(03)00034-0
-
S. Dreiseitl and L. Ohno-Machado, "Logistic regression and artificial neural network classification models: a methodology review," Journal of Biomedical Informatics, vol. 35, no. 5-6, pp. 352-359, 2002. (Pubitemid 36951935)
-
(2002)
Journal of Biomedical Informatics
, vol.35
, Issue.5-6
, pp. 352-359
-
-
Dreiseitl, S.1
Ohno-Machado, L.2
-
7
-
-
0029484103
-
Survey and critique of techniques for extracting rules from trained artificial neural networks
-
R. Andrews, J. Diederich, and A. B. Tickle, "Survey and critique of techniques for extracting rules from trained artificial neural networks," Knowledge-Based Systems, vol. 8, no. 6, pp. 373-389, 1995.
-
(1995)
Knowledge-based Systems
, vol.8
, Issue.6
, pp. 373-389
-
-
Andrews, R.1
Diederich, J.2
Tickle, A.B.3
-
10
-
-
78651433451
-
An investigation of the effect of the input representation in anfis modelling of breast cancer survival
-
H. Hamdan and J. M. Garibaldi, "An investigation of the effect of the input representation in anfis modelling of breast cancer survival," in the International Conference on Fuzzy Computation (ICFC 2010), pp. 99-104, 2010.
-
(2010)
The International Conference on Fuzzy Computation (ICFC 2010)
, pp. 99-104
-
-
Hamdan, H.1
Garibaldi, J.M.2
-
12
-
-
33748520872
-
Review: A gentle introduction to imputation of missing values
-
DOI 10.1016/j.jclinepi.2006.01.014, PII S0895435606001971
-
A. R. T. Donders, G. J. van der Heijden, T. Stijnen, and K. G. Moons, "Review: A gentle introduction to imputation of missing values," Journal of Clinical Epidemiology, vol. 59, no. 10, pp. 1087 - 1091, 2006. (Pubitemid 44374314)
-
(2006)
Journal of Clinical Epidemiology
, vol.59
, Issue.10
, pp. 1087-1091
-
-
Donders, A.R.T.1
Van Der Heijden, G.J.M.G.2
Stijnen, T.3
Moons, K.G.M.4
-
13
-
-
0037263771
-
Developing a prognostic model in the presence of missing data: An ovarian cancer case study
-
DOI 10.1016/S0895-4356(02)00539-5, PII S0895435602005395
-
T. G. Clark and D. G. Altman, "Developing a prognostic model in the presence of missing data: an ovarian cancer case study," Journal of Clinical Epidemiology, vol. 56, no. 1, pp. 28 - 37, 2003. (Pubitemid 36183312)
-
(2003)
Journal of Clinical Epidemiology
, vol.56
, Issue.1
, pp. 28-37
-
-
Clark, T.G.1
Altman, D.G.2
-
14
-
-
0038162240
-
A Bayesian neural network approach for modelling censored data with an application to prognosis after surgery for breast cancer
-
DOI 10.1016/S0933-3657(03)00033-2
-
P. J. G. Lisboa, H. Wong, P. Harris, and R. Swindell, "A bayesian neural network approach for modelling censored data with an application to prognosis after surgery for breast cancer," Artificial Intelligence in Medicine, vol. 28, no. 1, pp. 1-25, 2003. (Pubitemid 36870749)
-
(2003)
Artificial Intelligence in Medicine
, vol.28
, Issue.1
, pp. 1-25
-
-
Lisboa, P.J.G.1
Wong, H.2
Harris, P.3
Swindell, R.4
-
15
-
-
0000810783
-
Fuzzy clustering analysis for optimizing fuzzy membership functions
-
PII S0165011498002243
-
M.-S. Chen and S.-W. Wang, "Fuzzy clustering analysis for optimizing fuzzy membership functions," Fuzzy Sets and Systems, vol. 103, no. 2, pp. 239 - 254, 1999. (Pubitemid 129502322)
-
(1999)
Fuzzy Sets and Systems
, vol.103
, Issue.2
, pp. 239-254
-
-
Chen, M.-S.1
Wang, S.-W.2
-
16
-
-
79952361174
-
Optimising the fuzzy granulation of attribute domains
-
2009
-
M. E. Cintra, H. A. Camargo, and T. Martin, "Optimising the fuzzy granulation of attribute domains," in IFSA-EUSFLAT 2009, pp. 742-747, 2009.
-
(2009)
IFSA-EUSFLAT
, pp. 742-747
-
-
Cintra, M.E.1
Camargo, H.A.2
Martin, T.3
-
20
-
-
0035964608
-
A prognostic model for ovarian cancer
-
DOI 10.1038/sj.bjc.6692030
-
T. G. Clark, M. E. Stewart, D. G. Altman, G. H., and S. J. F, "A prognostic model for ovarian cancer," British Journal of Cancer, vol. 85, no. 7, pp. 944-952, 2001. (Pubitemid 33015994)
-
(2001)
British Journal of Cancer
, vol.85
, Issue.7
, pp. 944-952
-
-
Clark, T.G.1
Stewart, M.E.2
Altman, D.G.3
Gabra, H.4
Smyth, J.F.5
-
21
-
-
34548262351
-
PIEPOC: A new prognostic index for advanced epithelial ovarian cancer - Japan Multinational Trial Organization OC01-01
-
DOI 10.1200/JCO.2007.11.0114
-
S. Teramukai, K. Ochiai, H. Tada, and M. Fukushima, "Piepoc: A new prognostic index for advanced epithelial ovarian cancerjapan multinational trial organization oc01-01," Journal of Clinical Oncology, vol. 25, no. 22, pp. 3302-3306, 2007. (Pubitemid 47325616)
-
(2007)
Journal of Clinical Oncology
, vol.25
, Issue.22
, pp. 3302-3306
-
-
Teramukai, S.1
Ochiai, K.2
Tada, H.3
Fukushima, M.4
-
22
-
-
0038742791
-
Survival and prognostic factors in patients with ovarian cancer
-
DOI 10.1016/S0029-7844(03)00123-6
-
S. Tingulstad, F. E. Skjeldestad, T. Halvorsen, and B. Hagen, "Survival and prognostic factors in patients with ovarian cancer," Obstetrics & Gynecology, vol. 101, no. 5, pp. 885-891, 2003. (Pubitemid 36561249)
-
(2003)
Obstetrics and Gynecology
, vol.101
, Issue.5
, pp. 885-891
-
-
Tingulstad, S.1
Skjeldestad, F.E.2
Halvorsen, T.B.3
Hagen, B.4
-
23
-
-
0020396015
-
Toxicology and response criteria of the Eastern Cooperative Oncology Group
-
M. Oken, R. Creech, D. Tormey, J. Horton, T. Davis, E. McFadden, and P. Carbone, "Toxicity and response criteria of the eastern cooperative oncology group," Am J Clin Oncol, vol. 5, pp. 649-655, 1982. (Pubitemid 13149996)
-
(1982)
American Journal of Clinical Oncology: Cancer Clinical Trials
, vol.5
, Issue.6
, pp. 649-655
-
-
Oken, M.M.1
Creech, R.H.2
Davis, T.E.3
-
24
-
-
37649015340
-
Validation of a new prognostic index for advanced epithelial ovarian cancer: Results from its application to a uk-based cohort
-
T. G. Clark, M. Stewart, T. Rye, J. F. Smyth, and C. Gourley, "Validation of a new prognostic index for advanced epithelial ovarian cancer: results from its application to a uk-based cohort," Journal of Clinical Oncology, vol. 25, pp. 5669-70, 2007.
-
(2007)
Journal of Clinical Oncology
, vol.25
, pp. 5669-5670
-
-
Clark, T.G.1
Stewart, M.2
Rye, T.3
Smyth, J.F.4
Gourley, C.5
-
25
-
-
38049098404
-
Neural networks and other machine learning methods in cancer research
-
Springer Berlin / Heidelberg
-
A. Vellido and P. J. G. Lisboa, "Neural networks and other machine learning methods in cancer research," in Computational and Ambient Intelligence, vol. 4507, pp. 964-971, Springer Berlin / Heidelberg, 2007.
-
(2007)
Computational and Ambient Intelligence
, vol.4507
, pp. 964-971
-
-
Vellido, A.1
Lisboa, P.J.G.2
-
26
-
-
19344364327
-
Predicting breast cancer survivability: A comparison of three data mining methods
-
DOI 10.1016/j.artmed.2004.07.002, PII S0933365704001010
-
D. Delen, G. Walker, and A. Kadam, "Predicting breast cancer sur-vivability: a comparison of three data mining methods," Artificial Intelligence in Medicine, vol. 34, no. 2, pp. 113-127, 2005. (Pubitemid 40719029)
-
(2005)
Artificial Intelligence in Medicine
, vol.34
, Issue.2
, pp. 113-127
-
-
Delen, D.1
Walker, G.2
Kadam, A.3
-
27
-
-
76349086479
-
Data mining in cancer research-application notes
-
P. J. G. Lisboa, A. Vellido, R. Tagliaferri, F. Napolitano, M. Ceccarelli, D. M.-G. Jose, and E. Biganzoli, "Data mining in cancer research-application notes," IEEE Comp. Int. Mag., vol. 5, no. 1, pp. 14-18, 2010.
-
(2010)
IEEE Comp. Int. Mag.
, vol.5
, Issue.1
, pp. 14-18
-
-
Lisboa, P.J.G.1
Vellido, A.2
Tagliaferri, R.3
Napolitano, F.4
Ceccarelli, M.5
Jose, D.M.-G.6
Biganzoli, E.7
|