SCAMC : symposium on computer applications in medical care. USA, 1992.
A patient's intensive care unit (ICU) length of stay following cardiac surgery is an important issue in Canada, where cardiovascular intensive care resources are limited and waiting lists for cardiac surgery exist.
We trained a neural network with a database of 713 patients and 15 input variables to predict patients who would have a prolonged ICU length of stay, defined as a stay greater than 2 days.
In an independent test set of 696 patients, the network was able to stratify patients into three risk groups for prolonged stay (low, intermediate. and high), corresponding to frequencies of prolonged stay of 16.3, 35.3, and 60.8%, respectively.
Mots-clés Pascal : Durée, Chirurgie, Etude statistique, Hospitalisation, Soin intensif, Informatique biomédicale, Appareil circulatoire pathologie, Réseau neuronal, Prédiction, Gestion hospitalière, Homme, Canada, Amérique du Nord, Amérique, Assistance ordinateur
Mots-clés Pascal anglais : Duration, Surgery, Statistical study, Hospitalization, Intensive care, Biomedical data processing, Cardiovascular disease, Neural network, Prediction, Hospital management, Human, Canada, North America, America, Computer aid
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 93-0543571
Code Inist : 002B28E. Création : 199406.