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Titolo:
Clinical validation of an artificial neural network trained to identify acute allograft rejection in liver transplant recipients
Autore:
Hughes, VF; Melvin, DG; Niranjan, M; Alexander, GAM; Trull, AK;
Indirizzi:
Addenbrookes Hosp, Dept Clin Biochem, Cambridge CB2 2QQ, England Addenbrookes Hosp Cambridge England CB2 2QQ , Cambridge CB2 2QQ, England Addenbrookes Hosp, Dept Med, Cambridge CB2 2QQ, England Addenbrookes HospCambridge England CB2 2QQ , Cambridge CB2 2QQ, England Univ Cambridge, Dept Engn, Cambridge CB2 1PZ, England Univ Cambridge Cambridge England CB2 1PZ ngn, Cambridge CB2 1PZ, England
Titolo Testata:
LIVER TRANSPLANTATION
fascicolo: 6, volume: 7, anno: 2001,
pagine: 496 - 503
SICI:
1527-6465(200106)7:6<496:CVOAAN>2.0.ZU;2-2
Fonte:
ISI
Lingua:
ENG
Soggetto:
BLOOD CYCLOSPORINE CONCENTRATIONS; ACUTE MYOCARDIAL-INFARCTION; GLUTATHIONE S-TRANSFERASE; HEPATOCELLULAR DAMAGE; RISK-FACTORS; DIAGNOSIS; HEART; COMPUTER; TESTS; PHARMACODYNAMICS;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Clinical Medicine
Citazioni:
42
Recensione:
Indirizzi per estratti:
Indirizzo: Hughes, VF Addenbrookes Hosp, Dept Clin Biochem, Box 232,Hills Rd, Cambridge CB2 2QQ,England Addenbrookes Hosp Box 232,Hills Rd Cambridge England CB2 2QQ d
Citazione:
V.F. Hughes et al., "Clinical validation of an artificial neural network trained to identify acute allograft rejection in liver transplant recipients", LIVER TRANS, 7(6), 2001, pp. 496-503

Abstract

Artificial neural networks (ANNs) are techniques of nonlinear data modeling that have been studied in a wide variety of medical applications. An ANN was developed to assist in the diagnosis of acute rejection in liver transplant recipients. We investigated the diagnostic accuracy of this ANN on a new data set of patients from the same hospital. In addition, we compared the diagnostic accuracy of the ANN with that of the individual input variables (alanine aminotransferase [ALT] and bilirubin levels and day posttransplantation). Clinical and biochemical data were collected retrospectively for 124 consecutive liver transplantations (117 patients) over the first 3 months after transplantation. Diagnostic accuracy was calculated using receiveroperating characteristic (ROC) curve analysis. The ANN differentiated rejection from rejection-free episodes in the new data set over the first 3 months posttransplantation with an area under the ROC curve of 0.902 and sensitivity and specificity of 80.0% and 90.1% at the optimum decision threshold, respectively. The ANN was significantly more specific than ALT or bilirubin level or day posttransplantation at their corresponding optimum decisionthresholds (P < .0001). PeakANN output occurred 1 day earlier than peak values for either AUT or bilirubin (P < .005). The diagnostic accuracy of theANN was greater than that of any of the individual variables that had beenused as inputs. It would be a useful adjunct to conventional liver function tests for monitoring liver transplant recipients in the early postoperative period.

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Documento generato il 25/01/20 alle ore 19:26:48