141 related articles for article (PubMed ID: 9779891)
1. Predicting survival in malignant skin melanoma using Bayesian networks automatically induced by genetic algorithms. An empirical comparison between different approaches.
Sierra B; Larrañaga P
Artif Intell Med; 1998; 14(1-2):215-30. PubMed ID: 9779891
[TBL] [Abstract][Full Text] [Related]
2. Feature selection for optimized skin tumor recognition using genetic algorithms.
Handels H; Ross T; Kreusch J; Wolff HH; Pöppl SJ
Artif Intell Med; 1999 Jul; 16(3):283-97. PubMed ID: 10397305
[TBL] [Abstract][Full Text] [Related]
3. Comparing Bayesian neural network algorithms for classifying segmented outdoor images.
Vivarelli F; Williams CK
Neural Netw; 2001 May; 14(4-5):427-37. PubMed ID: 11411630
[TBL] [Abstract][Full Text] [Related]
4. A new machine learning classifier for high dimensional healthcare data.
Padman R; Bai X; Airoldi EM
Stud Health Technol Inform; 2007; 129(Pt 1):664-8. PubMed ID: 17911800
[TBL] [Abstract][Full Text] [Related]
5. Malignant melanoma detection by Bag-of-Features classification.
Situ N; Yuan X; Chen J; Zouridakis G
Annu Int Conf IEEE Eng Med Biol Soc; 2008; 2008():3110-3. PubMed ID: 19163365
[TBL] [Abstract][Full Text] [Related]
6. A comparison of Bayesian network learning algorithms from continuous data.
Fu LD; Tsamardinos I
AMIA Annu Symp Proc; 2005; 2005():960. PubMed ID: 16779247
[TBL] [Abstract][Full Text] [Related]
7. Analysis for warning factors of type 2 diabetes mellitus complications with Markov blanket based on a Bayesian network model.
Liu S; Zhang R; Shang X; Li W
Comput Methods Programs Biomed; 2020 May; 188():105302. PubMed ID: 31923820
[TBL] [Abstract][Full Text] [Related]
8. An evaluation of Bayesian techniques for controlling model complexity and selecting inputs in a neural network for short-term load forecasting.
Hippert HS; Taylor JW
Neural Netw; 2010 Apr; 23(3):386-95. PubMed ID: 20022462
[TBL] [Abstract][Full Text] [Related]
9. Novel Approaches for Diagnosing Melanoma Skin Lesions Through Supervised and Deep Learning Algorithms.
Premaladha J; Ravichandran KS
J Med Syst; 2016 Apr; 40(4):96. PubMed ID: 26872778
[TBL] [Abstract][Full Text] [Related]
10. Inferring Markov chains: Bayesian estimation, model comparison, entropy rate, and out-of-class modeling.
Strelioff CC; Crutchfield JP; Hübler AW
Phys Rev E Stat Nonlin Soft Matter Phys; 2007 Jul; 76(1 Pt 1):011106. PubMed ID: 17677409
[TBL] [Abstract][Full Text] [Related]
11. A hybrid random field model for scalable statistical learning.
Freno A; Trentin E; Gori M
Neural Netw; 2009; 22(5-6):603-13. PubMed ID: 19596548
[TBL] [Abstract][Full Text] [Related]
12. Predicting coronary artery disease with medical profile and gene polymorphisms data.
Chen Q; Li G; Leong TY; Heng CK
Stud Health Technol Inform; 2007; 129(Pt 2):1219-24. PubMed ID: 17911909
[TBL] [Abstract][Full Text] [Related]
13. Predicting the Survival of Gastric Cancer Patients Using Artificial and Bayesian Neural Networks.
Korhani Kangi A; Bahrampour A
Asian Pac J Cancer Prev; 2018 Feb; 19(2):487-490. PubMed ID: 29480983
[TBL] [Abstract][Full Text] [Related]
14. Employing decomposable partially observable Markov decision processes to control gene regulatory networks.
Erdogdu U; Polat F; Alhajj R
Artif Intell Med; 2017 Nov; 83():14-34. PubMed ID: 28733120
[TBL] [Abstract][Full Text] [Related]
15. Neural network models for conditional distribution under bayesian analysis.
Miazhynskaia T; Frühwirth-Schnatter S; Dorffner G
Neural Comput; 2008 Feb; 20(2):504-22. PubMed ID: 18045023
[TBL] [Abstract][Full Text] [Related]
16. Learning ensembles of neural networks by means of a Bayesian artificial immune system.
Castro PA; Von Zuben FJ
IEEE Trans Neural Netw; 2011 Feb; 22(2):304-16. PubMed ID: 21189236
[TBL] [Abstract][Full Text] [Related]
17. A comparison of learning algorithms for Bayesian networks: a case study based on data from an emergency medical service.
Acid S; de Campos LM; Fernández-Luna JM; Rodríguez S; María Rodríguez J; Luis Salcedo J
Artif Intell Med; 2004 Mar; 30(3):215-32. PubMed ID: 15081073
[TBL] [Abstract][Full Text] [Related]
18. Modelling survival after treatment of intraocular melanoma using artificial neural networks and Bayes theorem.
Taktak AF; Fisher AC; Damato BE
Phys Med Biol; 2004 Jan; 49(1):87-98. PubMed ID: 14971774
[TBL] [Abstract][Full Text] [Related]
19. Variational Bayesian approach to canonical correlation analysis.
Wang C
IEEE Trans Neural Netw; 2007 May; 18(3):905-10. PubMed ID: 17526355
[TBL] [Abstract][Full Text] [Related]
20. BELM: Bayesian extreme learning machine.
Soria-Olivas E; Gómez-Sanchis J; Martín JD; Vila-Francés J; Martínez M; Magdalena JR; Serrano AJ
IEEE Trans Neural Netw; 2011 Mar; 22(3):505-9. PubMed ID: 21257373
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
