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Titolo:
ARTIFICIAL NEURAL NETWORKS THAT USE SINGLE-PHOTON EMISSION TOMOGRAPHYTO IDENTIFY PATIENTS WITH PROBABLE ALZHEIMERS-DISEASE
Autore:
DAWSON MRW; DOBBS A; HOOPER HR; MCEWAN AJB; TRISCOTT J; COONEY J;
Indirizzi:
UNIV ALBERTA,DEPT PSYCHOL,BIOL COMPUTAT PROJECT EDMONTON T6G 2E9 AB CANADA CROSS CANC INST,DEPT NUCL MED EDMONTON AB CANADA UNIV ALBERTA,DEPT RADIOL & DIAGNOST IMAGING EDMONTON AB CANADA UNIV ALBERTA,DEPT FAMILY MED EDMONTON T6G 2E9 AB CANADA UNIV ALBERTA,DIV GERIATR MED EDMONTON T6G 2E9 AB CANADA UNIV ALBERTA,DEPT PSYCHIAT EDMONTON AB CANADA
Titolo Testata:
European journal of nuclear medicine
fascicolo: 12, volume: 21, anno: 1994,
pagine: 1303 - 1311
SICI:
0340-6997(1994)21:12<1303:ANNTUS>2.0.ZU;2-L
Fonte:
ISI
Lingua:
ENG
Soggetto:
CEREBRAL BLOOD-FLOW; COMPUTED-TOMOGRAPHY; HMPAO-SPECT; DEMENTIA; DIAGNOSIS;
Keywords:
ARTIFICIAL NEURAL NETWORKS; SINGLE-PHOTON EMISSION TOMOGRAPHY; ALZHEIMERS DISEASE;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Science Citation Index Expanded
Citazioni:
31
Recensione:
Indirizzi per estratti:
Citazione:
M.R.W. Dawson et al., "ARTIFICIAL NEURAL NETWORKS THAT USE SINGLE-PHOTON EMISSION TOMOGRAPHYTO IDENTIFY PATIENTS WITH PROBABLE ALZHEIMERS-DISEASE", European journal of nuclear medicine, 21(12), 1994, pp. 1303-1311

Abstract

Single-photon emission tomographic (SPET) images using technetium-99mlabelled hexamethylpropylene amine oxime were obtained from 97 patients diagnosed as having Alzheimer's disease, as well as from a comparison group of 64 normal subjects. Multiple linear regression was used topredict subject type (Alzheimer's vs comparison) using scintillation counts from 14 different brain regions as predictors, These results were disappointing: the regression equation accounted for only 33.5% of the variance between subjects. However, the same data were also used to train parallel distributed processing (PDP) networks of different sizes to classify subjects. In networks accounted for substantially more(up to 95%) of the variance in the data, and in many instances were able to distinguish perfectly between the two subjects, These results suggest two conclusions. First, SPET images do provide sufficient information to distinguish patients with Alzheimer's disease from a normal comparison group. Second, to access this diagnostic information, it appears that one must take advantage of the ability of PDP networks to detect higher-order nonlinear relationships among the predictor variables.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 27/01/20 alle ore 14:52:27