-
1
-
-
79952284127
-
Hallmarks of cancer: The next generation
-
D. Hanahan, and R.A. Weinberg Hallmarks of cancer: the next generation Cell 144 2011 646 674
-
(2011)
Cell
, vol.144
, pp. 646-674
-
-
Hanahan, D.1
Weinberg, R.A.2
-
2
-
-
84890541361
-
Statistical and practical considerations for clinical evaluation of predictive biomarkers
-
M.-Y.C. Polley, B. Freidlin, E.L. Korn, B.A. Conley, J.S. Abrams, and L.M. McShane Statistical and practical considerations for clinical evaluation of predictive biomarkers J Natl Cancer Inst 105 2013 1677 1683
-
(2013)
J Natl Cancer Inst
, vol.105
, pp. 1677-1683
-
-
Polley, M.-Y.C.1
Freidlin, B.2
Korn, E.L.3
Conley, B.A.4
Abrams, J.S.5
McShane, L.M.6
-
3
-
-
33744961676
-
Applications of machine learning in cancer prediction and prognosis
-
J.A. Cruz, and D.S. Wishart Applications of machine learning in cancer prediction and prognosis Cancer Informat 2 2006 59
-
(2006)
Cancer Informat
, vol.2
, pp. 59
-
-
Cruz, J.A.1
Wishart, D.S.2
-
4
-
-
84896920819
-
Assessment of circulating microRNAs in plasma of lung cancer patients
-
O. Fortunato, M. Boeri, C. Verri, D. Conte, M. Mensah, P. Suatoni, and et al. Assessment of circulating microRNAs in plasma of lung cancer patients Molecules 19 2014 3038 3054
-
(2014)
Molecules
, vol.19
, pp. 3038-3054
-
-
Fortunato, O.1
Boeri, M.2
Verri, C.3
Conte, D.4
Mensah, M.5
Suatoni, P.6
-
5
-
-
77956652041
-
MiRNAs as biomarkers and therapeutic targets in cancer
-
H.M. Heneghan, N. Miller, and M.J. Kerin MiRNAs as biomarkers and therapeutic targets in cancer Curr Opin Pharmacol 10 2010 543 550
-
(2010)
Curr Opin Pharmacol
, vol.10
, pp. 543-550
-
-
Heneghan, H.M.1
Miller, N.2
Kerin, M.J.3
-
6
-
-
84883525890
-
Cancer diagnosis and prognosis decoded by blood-based circulating microRNA signatures
-
D. Madhavan, K. Cuk, B. Burwinkel, and R. Yang Cancer diagnosis and prognosis decoded by blood-based circulating microRNA signatures Front Genet 4 2013
-
(2013)
Front Genet
, vol.4
-
-
Madhavan, D.1
Cuk, K.2
Burwinkel, B.3
Yang, R.4
-
7
-
-
84863259319
-
Circulating microRNAs: A novel class of biomarkers to diagnose and monitor human cancers
-
K. Zen, and C.Y. Zhang Circulating microRNAs: a novel class of biomarkers to diagnose and monitor human cancers Med Res Rev 32 2012 326 348
-
(2012)
Med Res Rev
, vol.32
, pp. 326-348
-
-
Zen, K.1
Zhang, C.Y.2
-
8
-
-
77953004083
-
Why most gene expression signatures of tumors have not been useful in the clinic
-
14 ps12-14 ps12
-
S. Koscielny Why most gene expression signatures of tumors have not been useful in the clinic Sci Transl Med 2 2010 [14 ps12-14 ps12]
-
(2010)
Sci Transl Med
, vol.2
-
-
Koscielny, S.1
-
9
-
-
13444249852
-
Prediction of cancer outcome with microarrays: A multiple random validation strategy
-
S. Michiels, S. Koscielny, and C. Hill Prediction of cancer outcome with microarrays: a multiple random validation strategy Lancet 365 2005 488 492
-
(2005)
Lancet
, vol.365
, pp. 488-492
-
-
Michiels, S.1
Koscielny, S.2
Hill, C.3
-
13
-
-
85137487254
-
Introduction to computational intelligence techniques and areas of their applications in medicine
-
A. Niknejad, and D. Petrovic Introduction to computational intelligence techniques and areas of their applications in medicine Med Appl Artif Intell 51 2013
-
(2013)
Med Appl Artif Intell
, vol.51
-
-
Niknejad, A.1
Petrovic, D.2
-
15
-
-
79952687473
-
Do two machine-learning based prognostic signatures for breast cancer capture the same biological processes?
-
Y. Drier, and E. Domany Do two machine-learning based prognostic signatures for breast cancer capture the same biological processes? PLoS One 6 2011 e17795
-
(2011)
PLoS One
, vol.6
-
-
Drier, Y.1
Domany, E.2
-
16
-
-
33846978784
-
Critical review of published microarray studies for cancer outcome and guidelines on statistical analysis and reporting
-
A. Dupuy, and R.M. Simon Critical review of published microarray studies for cancer outcome and guidelines on statistical analysis and reporting J Natl Cancer Inst 99 2007 147 157
-
(2007)
J Natl Cancer Inst
, vol.99
, pp. 147-157
-
-
Dupuy, A.1
Simon, R.M.2
-
17
-
-
13444282534
-
Outcome signature genes in breast cancer: Is there a unique set?
-
L. Ein-Dor, I. Kela, G. Getz, D. Givol, and E. Domany Outcome signature genes in breast cancer: is there a unique set? Bioinformatics 21 2005 171 178
-
(2005)
Bioinformatics
, vol.21
, pp. 171-178
-
-
Ein-Dor, L.1
Kela, I.2
Getz, G.3
Givol, D.4
Domany, E.5
-
18
-
-
33645825183
-
Thousands of samples are needed to generate a robust gene list for predicting outcome in cancer
-
L. Ein-Dor, O. Zuk, and E. Domany Thousands of samples are needed to generate a robust gene list for predicting outcome in cancer Proc Natl Acad Sci 103 2006 5923 5928
-
(2006)
Proc Natl Acad Sci
, vol.103
, pp. 5923-5928
-
-
Ein-Dor, L.1
Zuk, O.2
Domany, E.3
-
19
-
-
77954928071
-
Breast cancer risk estimation with artificial neural networks revisited
-
T. Ayer, O. Alagoz, J. Chhatwal, J.W. Shavlik, C.E. Kahn, and E.S. Burnside Breast cancer risk estimation with artificial neural networks revisited Cancer 116 2010 3310 3321
-
(2010)
Cancer
, vol.116
, pp. 3310-3321
-
-
Ayer, T.1
Alagoz, O.2
Chhatwal, J.3
Shavlik, J.W.4
Kahn, C.E.5
Burnside, E.S.6
-
22
-
-
0026604375
-
Neural networks and diagnosis in the clinical laboratory: State of the art
-
D. Cicchetti Neural networks and diagnosis in the clinical laboratory: state of the art Clin Chem 38 1992 9 10
-
(1992)
Clin Chem
, vol.38
, pp. 9-10
-
-
Cicchetti, D.1
-
23
-
-
0031158062
-
Prediction of outcome for patients with cutaneous melanoma
-
A.J. Cochran Prediction of outcome for patients with cutaneous melanoma Pigment Cell Res 10 1997 162 167
-
(1997)
Pigment Cell Res
, vol.10
, pp. 162-167
-
-
Cochran, A.J.1
-
24
-
-
84870869328
-
Multiparametric decision support system for the prediction of oral cancer reoccurrence
-
K.P. Exarchos, Y. Goletsis, and D.I. Fotiadis Multiparametric decision support system for the prediction of oral cancer reoccurrence IEEE Trans Inf Technol Biomed 16 2012 1127 1134
-
(2012)
IEEE Trans Inf Technol Biomed
, vol.16
, pp. 1127-1134
-
-
Exarchos, K.P.1
Goletsis, Y.2
Fotiadis, D.I.3
-
25
-
-
0034922742
-
Machine learning for medical diagnosis: History, state of the art and perspective
-
I. Kononenko Machine learning for medical diagnosis: history, state of the art and perspective Artif Intell Med 23 2001 89 109
-
(2001)
Artif Intell Med
, vol.23
, pp. 89-109
-
-
Kononenko, I.1
-
26
-
-
84888389162
-
Robust predictive model for evaluating breast cancer survivability
-
K. Park, A. Ali, D. Kim, Y. An, M. Kim, and H. Shin Robust predictive model for evaluating breast cancer survivability Engl Appl Artif Intell 26 2013 2194 2205
-
(2013)
Engl Appl Artif Intell
, vol.26
, pp. 2194-2205
-
-
Park, K.1
Ali, A.2
Kim, D.3
An, Y.4
Kim, M.5
Shin, H.6
-
27
-
-
33845881963
-
Improved breast cancer prognosis through the combination of clinical and genetic markers
-
Y. Sun, S. Goodison, J. Li, L. Liu, and W. Farmerie Improved breast cancer prognosis through the combination of clinical and genetic markers Bioinformatics 23 2007 30 37
-
(2007)
Bioinformatics
, vol.23
, pp. 30-37
-
-
Sun, Y.1
Goodison, S.2
Li, J.3
Liu, L.4
Farmerie, W.5
-
28
-
-
0030743761
-
Artificial neural networks applied to outcome prediction for colorectal cancer patients in separate institutions
-
L. Bottaci, P.J. Drew, J.E. Hartley, M.B. Hadfield, R. Farouk, P.WR. Lee, and et al. Artificial neural networks applied to outcome prediction for colorectal cancer patients in separate institutions Lancet 350 1997 469 472
-
(1997)
Lancet
, vol.350
, pp. 469-472
-
-
Bottaci, L.1
Drew, P.J.2
Hartley, J.E.3
Hadfield, M.B.4
Farouk, R.5
Lee, P.W.R.6
-
30
-
-
0021914514
-
Treatment selection for cancer patients: Application of statistical decision theory to the treatment of advanced ovarian cancer
-
R.J. Simes Treatment selection for cancer patients: application of statistical decision theory to the treatment of advanced ovarian cancer J Chronic Dis 38 1985 171 186
-
(1985)
J Chronic Dis
, vol.38
, pp. 171-186
-
-
Simes, R.J.1
-
31
-
-
56349089940
-
Support vector machines combined with feature selection for breast cancer diagnosis
-
M.F. Akay Support vector machines combined with feature selection for breast cancer diagnosis Expert Syst Appl 36 2009 3240 3247
-
(2009)
Expert Syst Appl
, vol.36
, pp. 3240-3247
-
-
Akay, M.F.1
-
32
-
-
84878374114
-
Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods
-
S.-W. Chang, S. Abdul-Kareem, A.F. Merican, and R.B. Zain Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods BMC Bioinforma 14 2013 170
-
(2013)
BMC Bioinforma
, vol.14
, pp. 170
-
-
Chang, S.-W.1
Abdul-Kareem, S.2
Merican, A.F.3
Zain, R.B.4
-
34
-
-
84894259615
-
Using three machine learning techniques for predicting breast cancer recurrence
-
A.T. Eshlaghy, A. Poorebrahimi, M. Ebrahimi, A.R. Razavi, and L.G. Ahmad Using three machine learning techniques for predicting breast cancer recurrence J Health Med Inform 4 2013 124
-
(2013)
J Health Med Inform
, vol.4
, pp. 124
-
-
Eshlaghy, A.T.1
Poorebrahimi, A.2
Ebrahimi, M.3
Razavi, A.R.4
Ahmad, L.G.5
-
35
-
-
84869866634
-
A multiscale and multiparametric approach for modeling the progression of oral cancer
-
K.P. Exarchos, Y. Goletsis, and D.I. Fotiadis A multiscale and multiparametric approach for modeling the progression of oral cancer BMC Med Inform Decis Mak 12 2012 136
-
(2012)
BMC Med Inform Decis Mak
, vol.12
, pp. 136
-
-
Exarchos, K.P.1
Goletsis, Y.2
Fotiadis, D.I.3
-
36
-
-
84882786709
-
Breast cancer survivability prediction using labeled, unlabeled, and pseudo-labeled patient data
-
J. Kim, and H. Shin Breast cancer survivability prediction using labeled, unlabeled, and pseudo-labeled patient data J Am Med Inform Assoc 20 2013 613 618
-
(2013)
J Am Med Inform Assoc
, vol.20
, pp. 613-618
-
-
Kim, J.1
Shin, H.2
-
37
-
-
0026668490
-
The future of prognostic factors in outcome prediction for patients with cancer
-
L.P. Fielding, C.M. Fenoglio-Preiser, and L.S. Freedman The future of prognostic factors in outcome prediction for patients with cancer Cancer 70 1992 2367 2377
-
(1992)
Cancer
, vol.70
, pp. 2367-2377
-
-
Fielding, L.P.1
Fenoglio-Preiser, C.M.2
Freedman, L.S.3
-
38
-
-
0037454225
-
Variations in lung cancer risk among smokers
-
P.B. Bach, M.W. Kattan, M.D. Thornquist, M.G. Kris, R.C. Tate, M.J. Barnett, and et al. Variations in lung cancer risk among smokers J Natl Cancer Inst 95 2003 470 478
-
(2003)
J Natl Cancer Inst
, vol.95
, pp. 470-478
-
-
Bach, P.B.1
Kattan, M.W.2
Thornquist, M.D.3
Kris, M.G.4
Tate, R.C.5
Barnett, M.J.6
-
39
-
-
0037441790
-
Application of breast cancer risk prediction models in clinical practice
-
S.M. Domchek, A. Eisen, K. Calzone, J. Stopfer, A. Blackwood, and B.L. Weber Application of breast cancer risk prediction models in clinical practice J Clin Oncol 21 2003 593 601
-
(2003)
J Clin Oncol
, vol.21
, pp. 593-601
-
-
Domchek, S.M.1
Eisen, A.2
Calzone, K.3
Stopfer, J.4
Blackwood, A.5
Weber, B.L.6
-
40
-
-
2942683357
-
Childhood obesity and hormonal abnormalities associated with cancer risk
-
F. Gascon, M. Valle, R. Martos, M. Zafra, R. Morales, and M.A. Castano Childhood obesity and hormonal abnormalities associated with cancer risk Eur J Cancer Prev 13 2004 193 197
-
(2004)
Eur J Cancer Prev
, vol.13
, pp. 193-197
-
-
Gascon, F.1
Valle, M.2
Martos, R.3
Zafra, M.4
Morales, R.5
Castano, M.A.6
-
41
-
-
84876394716
-
EllipsoidFN: A tool for identifying a heterogeneous set of cancer biomarkers based on gene expressions
-
X. Ren, Y. Wang, L. Chen, X.-S. Zhang, and Q. Jin ellipsoidFN: a tool for identifying a heterogeneous set of cancer biomarkers based on gene expressions Nucleic Acids Res 41 2013 e53
-
(2013)
Nucleic Acids Res
, vol.41
, pp. e53
-
-
Ren, X.1
Wang, Y.2
Chen, L.3
Zhang, X.-S.4
Jin, Q.5
-
42
-
-
84881484048
-
IPcc: A novel feature extraction method for accurate disease class discovery and prediction
-
X. Ren, Y. Wang, X.-S. Zhang, and Q. Jin iPcc: a novel feature extraction method for accurate disease class discovery and prediction Nucleic Acids Res 2013 gkt343
-
(2013)
Nucleic Acids Res
, pp. gkt343
-
-
Ren, X.1
Wang, Y.2
Zhang, X.-S.3
Jin, Q.4
-
43
-
-
84863104938
-
Revealing metabolite biomarkers for acupuncture treatment by linear programming based feature selection
-
Y. Wang, Q.-F. Wu, C. Chen, L.-Y. Wu, X.-Z. Yan, S.-G. Yu, and et al. Revealing metabolite biomarkers for acupuncture treatment by linear programming based feature selection BMC Syst Biol 6 2012 S15
-
(2012)
BMC Syst Biol
, vol.6
, pp. S15
-
-
Wang, Y.1
Wu, Q.-F.2
Chen, C.3
Wu, L.-Y.4
Yan, X.-Z.5
Yu, S.-G.6
-
44
-
-
84880442608
-
Predicting cancer susceptibility from single-nucleotide polymorphism data: A case study in multiple myeloma
-
M. Waddell, D. Page, and J. Shaughnessy Jr. Predicting cancer susceptibility from single-nucleotide polymorphism data: a case study in multiple myeloma ACM 2005 21 28
-
(2005)
ACM
, pp. 21-28
-
-
Waddell, M.1
Page, D.2
Shaughnessy, J.3
-
45
-
-
11144355509
-
Predictive models for breast cancer susceptibility from multiple single nucleotide polymorphisms
-
J. Listgarten, S. Damaraju, B. Poulin, L. Cook, J. Dufour, A. Driga, and et al. Predictive models for breast cancer susceptibility from multiple single nucleotide polymorphisms Clin Cancer Res 10 2004 2725 2737
-
(2004)
Clin Cancer Res
, vol.10
, pp. 2725-2737
-
-
Listgarten, J.1
Damaraju, S.2
Poulin, B.3
Cook, L.4
Dufour, J.5
Driga, A.6
-
46
-
-
79952407655
-
Development of a Bayesian belief network model for personalized prognostic risk assessment in colon carcinomatosis
-
A. Stojadinovic, A. Nissan, J. Eberhardt, T.C. Chua, J.O.W Pelz, and J. Esquivel Development of a Bayesian belief network model for personalized prognostic risk assessment in colon carcinomatosis Am Surg 77 2011 221 230
-
(2011)
Am Surg
, vol.77
, pp. 221-230
-
-
Stojadinovic, A.1
Nissan, A.2
Eberhardt, J.3
Chua, T.C.4
Pelz, J.O.W.5
Esquivel, J.6
-
47
-
-
84865143565
-
Development of novel breast cancer recurrence prediction model using support vector machine
-
W. Kim, K.S. Kim, J.E. Lee, D.-Y. Noh, S.-W. Kim, Y.S. Jung, and et al. Development of novel breast cancer recurrence prediction model using support vector machine J Breast Cancer 15 2012 230 238
-
(2012)
J Breast Cancer
, vol.15
, pp. 230-238
-
-
Kim, W.1
Kim, K.S.2
Lee, J.E.3
Noh, D.-Y.4
Kim, S.-W.5
Jung, Y.S.6
-
48
-
-
84900305562
-
Integrative gene network construction to analyze cancer recurrence using semi-supervised learning
-
C. Park, J. Ahn, H. Kim, and S. Park Integrative gene network construction to analyze cancer recurrence using semi-supervised learning PLoS One 9 2014 e86309
-
(2014)
PLoS One
, vol.9
-
-
Park, C.1
Ahn, J.2
Kim, H.3
Park, S.4
-
49
-
-
84898006454
-
Application of machine learning to predict the recurrence-proneness for cervical cancer
-
C.-J. Tseng, C.-J. Lu, C.-C. Chang, and G.-D. Chen Application of machine learning to predict the recurrence-proneness for cervical cancer Neural Comput & Applic 24 2014 1311 1316
-
(2014)
Neural Comput & Applic
, vol.24
, pp. 1311-1316
-
-
Tseng, C.-J.1
Lu, C.-J.2
Chang, C.-C.3
Chen, G.-D.4
-
50
-
-
84896347638
-
Risk classification of cancer survival using ANN with gene expression data from multiple laboratories
-
Y.-C. Chen, W.-C. Ke, and H.-W. Chiu Risk classification of cancer survival using ANN with gene expression data from multiple laboratories Comput Biol Med 48 2014 1 7
-
(2014)
Comput Biol Med
, vol.48
, pp. 1-7
-
-
Chen, Y.-C.1
Ke, W.-C.2
Chiu, H.-W.3
-
51
-
-
84886377492
-
A gene signature for breast cancer prognosis using support vector machine
-
X. Xu, Y. Zhang, L. Zou, M. Wang, and A. Li A gene signature for breast cancer prognosis using support vector machine IEEE 2012 928 931
-
(2012)
IEEE
, pp. 928-931
-
-
Xu, X.1
Zhang, Y.2
Zou, L.3
Wang, M.4
Li, A.5
-
52
-
-
33747891871
-
Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks
-
O. Gevaert, F. De Smet, D. Timmerman, Y. Moreau, and B. De Moor Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks Bioinformatics 22 2006 e184 e190
-
(2006)
Bioinformatics
, vol.22
, pp. e184-e190
-
-
Gevaert, O.1
De Smet, F.2
Timmerman, D.3
Moreau, Y.4
De Moor, B.5
-
53
-
-
84885039741
-
Survival model in oral squamous cell carcinoma based on clinicopathological parameters, molecular markers and support vector machines
-
P. Rosado, P. Lequerica-Fernández, L. Villallaín, I. Peña, F. Sanchez-Lasheras, and J.C. de Vicente Survival model in oral squamous cell carcinoma based on clinicopathological parameters, molecular markers and support vector machines Expert Syst Appl 40 2013 4770 4776
-
(2013)
Expert Syst Appl
, vol.40
, pp. 4770-4776
-
-
Rosado, P.1
Lequerica-Fernández, P.2
Villallaín, L.3
Peña, I.4
Sanchez-Lasheras, F.5
De Vicente, J.C.6
-
54
-
-
19344364327
-
Predicting breast cancer survivability: A comparison of three data mining methods
-
D. Delen, G. Walker, and A. Kadam Predicting breast cancer survivability: a comparison of three data mining methods Artif Intell Med 34 2005 113 127
-
(2005)
Artif Intell Med
, vol.34
, pp. 113-127
-
-
Delen, D.1
Walker, G.2
Kadam, A.3
-
55
-
-
84882384758
-
Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: A learning classifier system approach
-
R.J. Urbanowicz, A.S. Andrew, M.R. Karagas, and J.H. Moore Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approach J Am Med Inform Assoc 20 2013 603 612
-
(2013)
J Am Med Inform Assoc
, vol.20
, pp. 603-612
-
-
Urbanowicz, R.J.1
Andrew, A.S.2
Karagas, M.R.3
Moore, J.H.4
-
56
-
-
84898627404
-
Integrating domain knowledge in supervised machine learning to assess the risk of breast cancer
-
A. Bochare, A. Gangopadhyay, Y. Yesha, A. Joshi, Y. Yesha, M. Brady, and et al. Integrating domain knowledge in supervised machine learning to assess the risk of breast cancer Int J Med Eng Inform 6 2014 87 99
-
(2014)
Int J Med Eng Inform
, vol.6
, pp. 87-99
-
-
Bochare, A.1
Gangopadhyay, A.2
Yesha, Y.3
Joshi, A.4
Yesha, Y.5
Brady, M.6
-
57
-
-
77955736694
-
A support vector machine for decision support in melanoma recognition
-
S. Gilmore, R. Hofmann-Wellenhof, and H.P. Soyer A support vector machine for decision support in melanoma recognition Exp Dermatol 19 2010 830 835
-
(2010)
Exp Dermatol
, vol.19
, pp. 830-835
-
-
Gilmore, S.1
Hofmann-Wellenhof, R.2
Soyer, H.P.3
-
60
-
-
0031381525
-
Wrappers for feature subset selection
-
R. Kohavi, and G.H. John Wrappers for feature subset selection Artif Intell 97 1997 273 324
-
(1997)
Artif Intell
, vol.97
, pp. 273-324
-
-
Kohavi, R.1
John, G.H.2
-
62
-
-
33846064113
-
NCBI GEO: Mining tens of millions of expression profiles - Database and tools update
-
T. Barrett, D.B. Troup, S.E. Wilhite, P. Ledoux, D. Rudnev, C. Evangelista, and et al. NCBI GEO: mining tens of millions of expression profiles - database and tools update Nucleic Acids Res 35 2007 D760 D765
-
(2007)
Nucleic Acids Res
, vol.35
, pp. D760-D765
-
-
Barrett, T.1
Troup, D.B.2
Wilhite, S.E.3
Ledoux, P.4
Rudnev, D.5
Evangelista, C.6
-
63
-
-
75249101080
-
Evaluation of linguistic features useful in extraction of interactions from PubMed; Application to annotating known, high-throughput and predicted interactions in I2D
-
Y. Niu, D. Otasek, and I. Jurisica Evaluation of linguistic features useful in extraction of interactions from PubMed; application to annotating known, high-throughput and predicted interactions in I2D Bioinformatics 26 2010 111 119
-
(2010)
Bioinformatics
, vol.26
, pp. 111-119
-
-
Niu, Y.1
Otasek, D.2
Jurisica, I.3
-
64
-
-
84873928427
-
-
National Cancer Institute Bethesda, MD [Online]
-
N. Howlader, A. Noone, M. Krapcho, J. Garshell, N. Neyman, and S. Aletkruse SEER Cancer Statistics Review, 1975-2010, [Online] National Cancer Institute 2013 National Cancer Institute Bethesda, MD [Online]
-
(2013)
SEER Cancer Statistics Review, 1975-2010, [Online] National Cancer Institute
-
-
Howlader, N.1
Noone, A.2
Krapcho, M.3
Garshell, J.4
Neyman, N.5
Aletkruse, S.6
-
65
-
-
78651079671
-
-
X. Bian, J. Klemm, A. Basu, J. Hadfield, R. Srinivasa, T. Parnell, and et al. Data submission and curation for caArray, a standard based microarray data repository system 2009
-
(2009)
Data Submission and Curation for CaArray, a Standard Based Microarray Data Repository System
-
-
Bian, X.1
Klemm, J.2
Basu, A.3
Hadfield, J.4
Srinivasa, R.5
Parnell, T.6
-
66
-
-
53049094780
-
Improvement of microcalcification cluster detection in mammography utilizing image enhancement techniques
-
A. Papadopoulos, D.I. Fotiadis, and L. Costaridou Improvement of microcalcification cluster detection in mammography utilizing image enhancement techniques Comput Biol Med 38 2008 1045 1055
-
(2008)
Comput Biol Med
, vol.38
, pp. 1045-1055
-
-
Papadopoulos, A.1
Fotiadis, D.I.2
Costaridou, L.3
-
67
-
-
19344363582
-
Characterization of clustered microcalcifications in digitized mammograms using neural networks and support vector machines
-
A. Papadopoulos, D.I. Fotiadis, and A. Likas Characterization of clustered microcalcifications in digitized mammograms using neural networks and support vector machines Artif Intell Med 34 2005 141 150
-
(2005)
Artif Intell Med
, vol.34
, pp. 141-150
-
-
Papadopoulos, A.1
Fotiadis, D.I.2
Likas, A.3
-
68
-
-
84877734926
-
Improving breast cancer survival analysis through competition-based multidimensional modeling
-
E. Bilal, J. Dutkowski, J. Guinney, I.S. Jang, B.A. Logsdon, G. Pandey, and et al. Improving breast cancer survival analysis through competition-based multidimensional modeling PLoS Comput Biol 9 2013 e1003047
-
(2013)
PLoS Comput Biol
, vol.9
-
-
Bilal, E.1
Dutkowski, J.2
Guinney, J.3
Jang, I.S.4
Logsdon, B.A.5
Pandey, G.6
-
69
-
-
81155133281
-
Prognostic value of a combined estrogen receptor, progesterone receptor, Ki-67, and human epidermal growth factor receptor 2 immunohistochemical score and comparison with the Genomic Health recurrence score in early breast cancer
-
J. Cuzick, M. Dowsett, S. Pineda, C. Wale, J. Salter, E. Quinn, and et al. Prognostic value of a combined estrogen receptor, progesterone receptor, Ki-67, and human epidermal growth factor receptor 2 immunohistochemical score and comparison with the Genomic Health recurrence score in early breast cancer J Clin Oncol 29 2011 4273 4278
-
(2011)
J Clin Oncol
, vol.29
, pp. 4273-4278
-
-
Cuzick, J.1
Dowsett, M.2
Pineda, S.3
Wale, C.4
Salter, J.5
Quinn, E.6
-
70
-
-
62449131093
-
Supervised risk predictor of breast cancer based on intrinsic subtypes
-
J.S. Parker, M. Mullins, M.C. Cheang, S. Leung, D. Voduc, T. Vickery, and et al. Supervised risk predictor of breast cancer based on intrinsic subtypes J Clin Oncol 27 2009 1160 1167
-
(2009)
J Clin Oncol
, vol.27
, pp. 1160-1167
-
-
Parker, J.S.1
Mullins, M.2
Cheang, M.C.3
Leung, S.4
Voduc, D.5
Vickery, T.6
-
71
-
-
19944422061
-
A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer
-
S. Paik, S. Shak, G. Tang, C. Kim, J. Baker, M. Cronin, and et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer N Engl J Med 351 2004 2817 2826
-
(2004)
N Engl J Med
, vol.351
, pp. 2817-2826
-
-
Paik, S.1
Shak, S.2
Tang, G.3
Kim, C.4
Baker, J.5
Cronin, M.6
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