121 related articles for article (PubMed ID: 21272346)
1. Statistical learning techniques applied to epidemiology: a simulated case-control comparison study with logistic regression.
Heine JJ; Land WH; Egan KM
BMC Bioinformatics; 2011 Jan; 12():37. PubMed ID: 21272346
[TBL] [Abstract][Full Text] [Related]
2. Part 1. Statistical Learning Methods for the Effects of Multiple Air Pollution Constituents.
Coull BA; Bobb JF; Wellenius GA; Kioumourtzoglou MA; Mittleman MA; Koutrakis P; Godleski JJ
Res Rep Health Eff Inst; 2015 Jun; (183 Pt 1-2):5-50. PubMed ID: 26333238
[TBL] [Abstract][Full Text] [Related]
3. Statistical learning methods as a preprocessing step for survival analysis: evaluation of concept using lung cancer data.
Behera M; Fowler EE; Owonikoko TK; Land WH; Mayfield W; Chen Z; Khuri FR; Ramalingam SS; Heine JJ
Biomed Eng Online; 2011 Nov; 10():97. PubMed ID: 22067671
[TBL] [Abstract][Full Text] [Related]
4. Predicting radiotherapy outcomes using statistical learning techniques.
El Naqa I; Bradley JD; Lindsay PE; Hope AJ; Deasy JO
Phys Med Biol; 2009 Sep; 54(18):S9-S30. PubMed ID: 19687564
[TBL] [Abstract][Full Text] [Related]
5. Artificial neural networks modeling gene-environment interaction.
Günther F; Pigeot I; Bammann K
BMC Genet; 2012 May; 13():37. PubMed ID: 22583704
[TBL] [Abstract][Full Text] [Related]
6. Method of regulatory network that can explore protein regulations for disease classification.
Wang HQ; Zhu HL; Cho WC; Yip TT; Ngan RK; Law SC
Artif Intell Med; 2010; 48(2-3):119-27. PubMed ID: 19962281
[TBL] [Abstract][Full Text] [Related]
7. Comparing artificial neural networks, general linear models and support vector machines in building predictive models for small interfering RNAs.
McQuisten KA; Peek AS
PLoS One; 2009 Oct; 4(10):e7522. PubMed ID: 19847297
[TBL] [Abstract][Full Text] [Related]
8. [Methodological approach to the use of artificial neural networks for predicting results in medicine].
Trujillano J; March J; Sorribas A
Med Clin (Barc); 2004; 122 Suppl 1():59-67. PubMed ID: 14980162
[TBL] [Abstract][Full Text] [Related]
9. Binomial Logistic Regression and Artificial Neural Network Methods to Classify Opioid-Dependent Subjects and Control Group Using Quantitative EEG Power Measures.
Erguzel TT; Noyan CO; Eryilmaz G; Ünsalver BÖ; Cebi M; Tas C; Dilbaz N; Tarhan N
Clin EEG Neurosci; 2019 Sep; 50(5):303-310. PubMed ID: 30642219
[TBL] [Abstract][Full Text] [Related]
10. Prediction of malignant breast lesions from MRI features: a comparison of artificial neural network and logistic regression techniques.
McLaren CE; Chen WP; Nie K; Su MY
Acad Radiol; 2009 Jul; 16(7):842-51. PubMed ID: 19409817
[TBL] [Abstract][Full Text] [Related]
11. Logistic regression by means of evolutionary radial basis function neural networks.
Gutierrez PA; Hervas-Martinez C; Martinez-Estudillo FJ
IEEE Trans Neural Netw; 2011 Feb; 22(2):246-63. PubMed ID: 21138802
[TBL] [Abstract][Full Text] [Related]
12. Evaluating heterogeneity in indoor and outdoor air pollution using land-use regression and constrained factor analysis.
Levy JI; Clougherty JE; Baxter LK; Houseman EA; Paciorek CJ;
Res Rep Health Eff Inst; 2010 Dec; (152):5-80; discussion 81-91. PubMed ID: 21409949
[TBL] [Abstract][Full Text] [Related]
13. A set of SAS macros for calculating and displaying adjusted odds ratios (with confidence intervals) for continuous covariates in logistic B-spline regression models.
Gregory M; Ulmer H; Pfeiffer KP; Lang S; Strasak AM
Comput Methods Programs Biomed; 2008 Oct; 92(1):109-14. PubMed ID: 18603325
[TBL] [Abstract][Full Text] [Related]
14. Prediction of Chronic Lower Back Pain Using the Hierarchical Neural Network: Comparison with Logistic Regression-A Pilot Study.
Owari Y; Miyatake N
Medicina (Kaunas); 2019 Jun; 55(6):. PubMed ID: 31181815
[No Abstract] [Full Text] [Related]
15. Comparing an Artificial Neural Network to Logistic Regression for Predicting ED Visit Risk Among Patients With Cancer: A Population-Based Cohort Study.
Sutradhar R; Barbera L
J Pain Symptom Manage; 2020 Jul; 60(1):1-9. PubMed ID: 32088358
[TBL] [Abstract][Full Text] [Related]
16. Ambient Air Pollution and Adverse Pregnancy Outcomes in Wuhan, China.
Qian Z; Zhang B; Liang S; Wang J; Yang S; Hu K; Trevathan E; Yang R; Li Q; Flick LH; Hu R; Huang Z; Zhang Y; Hu S; Wang J; Shen L; Lu Y; Peng H; Yu Y; Yang L; Chen W; Liu W; Zhang W
Res Rep Health Eff Inst; 2016 Sep; (189):1-65. PubMed ID: 29659240
[TBL] [Abstract][Full Text] [Related]
17. Comparison of machine learning techniques with classical statistical models in predicting health outcomes.
Song X; Mitnitski A; Cox J; Rockwood K
Stud Health Technol Inform; 2004; 107(Pt 1):736-40. PubMed ID: 15360910
[TBL] [Abstract][Full Text] [Related]
18. Performance comparison between Logistic regression, decision trees, and multilayer perceptron in predicting peripheral neuropathy in type 2 diabetes mellitus.
Li CP; Zhi XY; Ma J; Cui Z; Zhu ZL; Zhang C; Hu LP
Chin Med J (Engl); 2012 Mar; 125(5):851-7. PubMed ID: 22490586
[TBL] [Abstract][Full Text] [Related]
19. Fuzzy jump wavelet neural network based on rule induction for dynamic nonlinear system identification with real data applications.
Kharazihai Isfahani M; Zekri M; Marateb HR; Mañanas MA
PLoS One; 2019; 14(12):e0224075. PubMed ID: 31816627
[TBL] [Abstract][Full Text] [Related]
20. Coupling K-nearest neighbors with logistic regression in case-based reasoning.
Campillo-Gimenez B; Bayat S; Cuggia M
Stud Health Technol Inform; 2012; 180():275-9. PubMed ID: 22874195
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
