283 related articles for article (PubMed ID: 14684266)
1. Use of genetic algorithms for neural networks to predict community-acquired pneumonia.
Heckerling PS; Gerber BS; Tape TG; Wigton RS
Artif Intell Med; 2004 Jan; 30(1):71-84. PubMed ID: 14684266
[TBL] [Abstract][Full Text] [Related]
2. Prediction of community-acquired pneumonia using artificial neural networks.
Heckerling PS; Gerber BS; Tape TG; Wigton RS
Med Decis Making; 2003; 23(2):112-21. PubMed ID: 12693873
[TBL] [Abstract][Full Text] [Related]
3. Selection of predictor variables for pneumonia using neural networks and genetic algorithms.
Heckerling PS; Gerber BS; Tape TG; Wigton RS
Methods Inf Med; 2005; 44(1):89-97. PubMed ID: 15778799
[TBL] [Abstract][Full Text] [Related]
4. An artificial neural network as a model for prediction of survival in trauma patients: validation for a regional trauma area.
DiRusso SM; Sullivan T; Holly C; Cuff SN; Savino J
J Trauma; 2000 Aug; 49(2):212-20; discussion 220-3. PubMed ID: 10963531
[TBL] [Abstract][Full Text] [Related]
5. An artificial neural network for predicting the incidence of radiation pneumonitis.
Su M; Miften M; Whiddon C; Sun X; Light K; Marks L
Med Phys; 2005 Feb; 32(2):318-25. PubMed ID: 15789575
[TBL] [Abstract][Full Text] [Related]
6. Artificial Neural Networks for differential diagnosis of breast lesions in MR-Mammography: a systematic approach addressing the influence of network architecture on diagnostic performance using a large clinical database.
Dietzel M; Baltzer PA; Dietzel A; Zoubi R; Gröschel T; Burmeister HP; Bogdan M; Kaiser WA
Eur J Radiol; 2012 Jul; 81(7):1508-13. PubMed ID: 21459533
[TBL] [Abstract][Full Text] [Related]
7. Predicting outcomes in patients with perforated gastroduodenal ulcers: artificial neural network modelling indicates a highly complex disease.
Søreide K; Thorsen K; Søreide JA
Eur J Trauma Emerg Surg; 2015 Feb; 41(1):91-8. PubMed ID: 25621078
[TBL] [Abstract][Full Text] [Related]
8. Application of artificial neural networks to establish a predictive mortality risk model in children admitted to a paediatric intensive care unit.
Chan CH; Chan EY; Ng DK; Chow PY; Kwok KL
Singapore Med J; 2006 Nov; 47(11):928-34. PubMed ID: 17075658
[TBL] [Abstract][Full Text] [Related]
9. Identification of spinal deformity classification with total curvature analysis and artificial neural network.
Lin H
IEEE Trans Biomed Eng; 2008 Jan; 55(1):376-82. PubMed ID: 18232388
[TBL] [Abstract][Full Text] [Related]
10. A multifactorial analysis of obesity as CVD risk factor: use of neural network based methods in a nutrigenetics context.
Valavanis IK; Mougiakakou SG; Grimaldi KA; Nikita KS
BMC Bioinformatics; 2010 Sep; 11():453. PubMed ID: 20825661
[TBL] [Abstract][Full Text] [Related]
11. Application of preoperative artificial neural network based on blood biomarkers and clinicopathological parameters for predicting long-term survival of patients with gastric cancer.
Que SJ; Chen QY; Qing-Zhong ; Liu ZY; Wang JB; Lin JX; Lu J; Cao LL; Lin M; Tu RH; Huang ZN; Lin JL; Zheng HL; Li P; Zheng CH; Huang CM; Xie JW
World J Gastroenterol; 2019 Nov; 25(43):6451-6464. PubMed ID: 31798281
[TBL] [Abstract][Full Text] [Related]
12. Genetic algorithm pruning of probabilistic neural networks in medical disease estimation.
Mantzaris D; Anastassopoulos G; Adamopoulos A
Neural Netw; 2011 Oct; 24(8):831-5. PubMed ID: 21723704
[TBL] [Abstract][Full Text] [Related]
13. A new constructive algorithm for architectural and functional adaptation of artificial neural networks.
Islam MM; Sattar MA; Amin MF; Yao X; Murase K
IEEE Trans Syst Man Cybern B Cybern; 2009 Dec; 39(6):1590-605. PubMed ID: 19502131
[TBL] [Abstract][Full Text] [Related]
14. Predictors of urinary tract infection based on artificial neural networks and genetic algorithms.
Heckerling PS; Canaris GJ; Flach SD; Tape TG; Wigton RS; Gerber BS
Int J Med Inform; 2007 Apr; 76(4):289-96. PubMed ID: 16469531
[TBL] [Abstract][Full Text] [Related]
15. [Artificial neural network forecasting method in monitoring technique by spectrometric oil analysis].
Yang YW; Chen G; Yang YW; Chen G
Guang Pu Xue Yu Guang Pu Fen Xi; 2005 Aug; 25(8):1339-43. PubMed ID: 16329517
[TBL] [Abstract][Full Text] [Related]
16. Usefulness of artificial neural network for differential diagnosis of hepatic masses on CT images.
Matake K; Yoshimitsu K; Kumazawa S; Higashida Y; Irie H; Asayama Y; Nakayama T; Kakihara D; Katsuragawa S; Doi K; Honda H
Acad Radiol; 2006 Aug; 13(8):951-62. PubMed ID: 16843847
[TBL] [Abstract][Full Text] [Related]
17. Improvement in the Prediction of Ventilator Weaning Outcomes by an Artificial Neural Network in a Medical ICU.
Kuo HJ; Chiu HW; Lee CN; Chen TT; Chang CC; Bien MY
Respir Care; 2015 Nov; 60(11):1560-9. PubMed ID: 26329358
[TBL] [Abstract][Full Text] [Related]
18. Prediction of persistent hemodynamic depression after carotid angioplasty and stenting using artificial neural network model.
Jeon JP; Kim C; Oh BD; Kim SJ; Kim YS
Clin Neurol Neurosurg; 2018 Jan; 164():127-131. PubMed ID: 29223792
[TBL] [Abstract][Full Text] [Related]
19. Predicting coronary artery disease: a comparison between two data mining algorithms.
Ayatollahi H; Gholamhosseini L; Salehi M
BMC Public Health; 2019 Apr; 19(1):448. PubMed ID: 31035958
[TBL] [Abstract][Full Text] [Related]
20. Optimisation of ANN topology for predicting the rehydrated apple cubes colour change using RSM and GA.
Winiczenko R; Górnicki K; Kaleta A; Janaszek-Mańkowska M
Neural Comput Appl; 2018; 30(6):1795-1809. PubMed ID: 30220793
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]