Neural networks trained with simulation data for outcome prediction in pallidotomy for Parkinson's disease

Autor:	Richard M. Lehman, Evangelia Micheli-Tzanakou, Jennifer L. Hamilton
Rok vydání:	2002
Předmět:	Flexibility (engineering) Parkinson's disease Artificial neural network business.industry Computer science medicine.medical_treatment medicine.disease Machine learning computer.software_genre Outcome (game theory) medicine Pallidotomy Artificial intelligence business Outcome prediction computer
Zdroj:	Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143).
DOI:	10.1109/iembs.2000.900652
Popis:	Neural networks were trained using the ALOPEX technique to predict the outcome of pallidotomy, an operation performed to alleviate Parkinson's disease. Because of the limited number of operations performed, the training procedure relied heavily on simulation data. The assumptions from which the simulation data were derived were reflected in the performance of the resultant networks; the networks nonetheless retained the flexibility to respond appropriately to unusual inputs.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::e921a5d7b654c873b0322303e5bd8568 https://doi.org/10.1109/iembs.2000.900652 Zobrazit plný text záznamu