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Items: 1 to 20 of 96

1.

Unbiased Prediction and Feature Selection in High-Dimensional Survival Regression.

Laimighofer M, Krumsiek J, Buettner F, Theis FJ.

J Comput Biol. 2016 Apr;23(4):279-90. doi: 10.1089/cmb.2015.0192. Epub 2016 Feb 19.

2.

Predicting censored survival data based on the interactions between meta-dimensional omics data in breast cancer.

Kim D, Li R, Dudek SM, Ritchie MD.

J Biomed Inform. 2015 Aug;56:220-8. doi: 10.1016/j.jbi.2015.05.019. Epub 2015 Jun 3.

3.
4.

Deviance residuals-based sparse PLS and sparse kernel PLS regression for censored data.

Bastien P, Bertrand F, Meyer N, Maumy-Bertrand M.

Bioinformatics. 2015 Feb 1;31(3):397-404. doi: 10.1093/bioinformatics/btu660. Epub 2014 Oct 6.

PMID:
25286920
5.

Feature selection and survival modeling in The Cancer Genome Atlas.

Kim H, Bredel M.

Int J Nanomedicine. 2013;8 Suppl 1:57-62. doi: 10.2147/IJN.S40733. Epub 2013 Sep 16.

6.

Mixture classification model based on clinical markers for breast cancer prognosis.

Zeng T, Liu J.

Artif Intell Med. 2010 Feb-Mar;48(2-3):129-37. doi: 10.1016/j.artmed.2009.07.008. Epub 2009 Dec 14.

PMID:
20005686
7.

Unbiased descriptor and parameter selection confirms the potential of proteochemometric modelling.

Freyhult E, Prusis P, Lapinsh M, Wikberg JE, Moulton V, Gustafsson MG.

BMC Bioinformatics. 2005 Mar 10;6:50.

8.

The feature selection bias problem in relation to high-dimensional gene data.

Krawczuk J, Łukaszuk T.

Artif Intell Med. 2016 Jan;66:63-71. doi: 10.1016/j.artmed.2015.11.001. Epub 2015 Nov 14.

PMID:
26674595
9.

Survival Prediction and Feature Selection in Patients with Breast Cancer Using Support Vector Regression.

Goli S, Mahjub H, Faradmal J, Mashayekhi H, Soltanian AR.

Comput Math Methods Med. 2016;2016:2157984. Epub 2016 Nov 1.

10.

Network-based survival analysis reveals subnetwork signatures for predicting outcomes of ovarian cancer treatment.

Zhang W, Ota T, Shridhar V, Chien J, Wu B, Kuang R.

PLoS Comput Biol. 2013;9(3):e1002975. doi: 10.1371/journal.pcbi.1002975. Epub 2013 Mar 21.

11.

Pathway-based classification of cancer subtypes.

Kim S, Kon M, DeLisi C.

Biol Direct. 2012 Jul 3;7:21. doi: 10.1186/1745-6150-7-21.

12.

Machine learning models in breast cancer survival prediction.

Montazeri M, Montazeri M, Montazeri M, Beigzadeh A.

Technol Health Care. 2016;24(1):31-42. doi: 10.3233/THC-151071.

PMID:
26409558
13.

Derivation of molecular signatures for breast cancer recurrence prediction using a two-way validation approach.

Sun Y, Urquidi V, Goodison S.

Breast Cancer Res Treat. 2010 Feb;119(3):593-9. doi: 10.1007/s10549-009-0365-6. Epub 2009 Mar 17.

14.

Investigating the prediction ability of survival models based on both clinical and omics data: two case studies.

De Bin R, Sauerbrei W, Boulesteix AL.

Stat Med. 2014 Dec 30;33(30):5310-29. doi: 10.1002/sim.6246. Epub 2014 Jul 9.

PMID:
25042390
15.

Recursive SVM biomarker selection for early detection of breast cancer in peripheral blood.

Zhang F, Kaufman HL, Deng Y, Drabier R.

BMC Med Genomics. 2013;6 Suppl 1:S4. doi: 10.1186/1755-8794-6-S1-S4. Epub 2013 Jan 23.

16.

Stable Gene Signature Selection for Prediction of Breast Cancer Recurrence Using Joint Mutual Information.

Sehhati M, Mehridehnavi A, Rabbani H, Pourhossein M.

IEEE/ACM Trans Comput Biol Bioinform. 2015 Nov-Dec;12(6):1440-8. doi: 10.1109/TCBB.2015.2407407.

PMID:
26671813
17.

A novel feature ranking method for prediction of cancer stages using proteomics data.

Saghapour E, Kermani S, Sehhati M.

PLoS One. 2017 Sep 21;12(9):e0184203. doi: 10.1371/journal.pone.0184203. eCollection 2017.

18.

compound.Cox: Univariate feature selection and compound covariate for predicting survival.

Emura T, Matsui S, Chen HY.

Comput Methods Programs Biomed. 2019 Jan;168:21-37. doi: 10.1016/j.cmpb.2018.10.020. Epub 2018 Oct 27.

PMID:
30527130
19.

Logistic regression for disease classification using microarray data: model selection in a large p and small n case.

Liao JG, Chin KV.

Bioinformatics. 2007 Aug 1;23(15):1945-51. Epub 2007 May 31.

PMID:
17540680
20.

Prediction of early breast cancer metastasis from DNA microarray data using high-dimensional cox regression models.

Zemmour C, Bertucci F, Finetti P, Chetrit B, Birnbaum D, Filleron T, Boher JM.

Cancer Inform. 2015 May 5;14(Suppl 2):129-38. doi: 10.4137/CIN.S17284. eCollection 2015.

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