These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
68 related articles for article (PubMed ID: 7934708)
21. Bootstrapping confidence intervals for clinical input variable effects in a network trained to identify the presence of acute myocardial infarction. Baxt WG; White H Neural Comput; 1995 May; 7(3):624-38. PubMed ID: 8935962 [No Abstract] [Full Text] [Related]
22. Evaluating variable selection methods for diagnosis of myocardial infarction. Dreiseitl S; Ohno-Machado L; Vinterbo S Proc AMIA Symp; 1999; ():246-50. PubMed ID: 10566358 [TBL] [Abstract][Full Text] [Related]
23. Clinical validation of an artificial neural network trained to identify acute allograft rejection in liver transplant recipients. Hughes VF; Melvin DG; Niranjan M; Alexander GA; Trull AK Liver Transpl; 2001 Jun; 7(6):496-503. PubMed ID: 11443576 [TBL] [Abstract][Full Text] [Related]
24. Application of artificial neural networks to clinical medicine. Baxt WG Lancet; 1995 Oct; 346(8983):1135-8. PubMed ID: 7475607 [No Abstract] [Full Text] [Related]
25. [ECG signal analysis by pattern comparison and ECG databanks]. Kreiseler D; Bousseljot R Biomed Tech (Berl); 1998; 43 Suppl 3():73-6. PubMed ID: 11776227 [No Abstract] [Full Text] [Related]
26. Artificial neural network algorithms for early diagnosis of acute myocardial infarction and prediction of infarct size in chest pain patients. Eggers KM; Ellenius J; Dellborg M; Groth T; Oldgren J; Swahn E; Lindahl B Int J Cardiol; 2007 Jan; 114(3):366-74. PubMed ID: 16797088 [TBL] [Abstract][Full Text] [Related]
27. How can a massive training artificial neural network (MTANN) be trained with a small number of cases in the distinction between nodules and vessels in thoracic CT? Suzuki K; Doi K Acad Radiol; 2005 Oct; 12(10):1333-41. PubMed ID: 16179210 [TBL] [Abstract][Full Text] [Related]
28. Automatic detection of epileptiform events in EEG by a three-stage procedure based on artificial neural networks. Acir N; Oztura I; Kuntalp M; Baklan B; Güzeliş C IEEE Trans Biomed Eng; 2005 Jan; 52(1):30-40. PubMed ID: 15651562 [TBL] [Abstract][Full Text] [Related]
29. 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]
30. Noninvasive prediction of sudden death and sustained ventricular tachycardia after acute myocardial infarction using a neural network algorithm. Zoni-Berisso M; Molini D; Viani S; Mela GS; Delfino L Ital Heart J; 2001 Aug; 2(8):612-20. PubMed ID: 11577836 [TBL] [Abstract][Full Text] [Related]
31. Using an artificial neural network to detect activations during ventricular fibrillation. Young MT; Blanchard SM; White MW; Johnson EE; Smith WM; Ideker RE Comput Biomed Res; 2000 Feb; 33(1):43-58. PubMed ID: 10772783 [TBL] [Abstract][Full Text] [Related]
32. Novel solutions for an old disease: diagnosis of acute appendicitis with random forest, support vector machines, and artificial neural networks. Hsieh CH; Lu RH; Lee NH; Chiu WT; Hsu MH; Li YC Surgery; 2011 Jan; 149(1):87-93. PubMed ID: 20466403 [TBL] [Abstract][Full Text] [Related]
33. Acute appendicitis diagnosis using artificial neural networks. Park SY; Kim SM Technol Health Care; 2015; 23 Suppl 2():S559-65. PubMed ID: 26410524 [TBL] [Abstract][Full Text] [Related]
34. 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]
35. Artificial neural networks: current status in cardiovascular medicine. Itchhaporia D; Snow PB; Almassy RJ; Oetgen WJ J Am Coll Cardiol; 1996 Aug; 28(2):515-21. PubMed ID: 8800133 [TBL] [Abstract][Full Text] [Related]
36. Application of serum protein fingerprinting coupled with artificial neural network model in diagnosis of hepatocellular carcinoma. Wang JX; Zhang B; Yu JK; Liu J; Yang MQ; Zheng S Chin Med J (Engl); 2005 Aug; 118(15):1278-84. PubMed ID: 16117882 [TBL] [Abstract][Full Text] [Related]
37. Effects of input data on the performance of a neural network in distinguishing normal and glaucomatous visual fields. Bengtsson B; Bizios D; Heijl A Invest Ophthalmol Vis Sci; 2005 Oct; 46(10):3730-6. PubMed ID: 16186356 [TBL] [Abstract][Full Text] [Related]
38. [Evaluation system for collecting diagnostic information from signals and data of medical sensor systems]. Bousseljot RD; Kreiseler D Biomed Tech (Berl); 1997; 42 Suppl():407-8. PubMed ID: 9517212 [No Abstract] [Full Text] [Related]