Automatic Diagnosis of the Footprint Pathologies Based on Neural Networks

Autor:	Mary Carmen Jarur, Daniel Sbarbaro, Marco Mora
Rok vydání:	2007
Předmět:	Footprint Artificial neural network Computer science business.industry Artificial intelligence Machine learning computer.software_genre business computer
Zdroj:	Adaptive and Natural Computing Algorithms ISBN: 9783540715900 ICANNGA (2)
Popis:	Currently foot pathologies, like cave and flat foot, are detected by an human expert who interprets a footprint image. The lack of trained personal to carry out massive first screening detection campaigns precludes the routinary diagnostic of these pathologies. This work presents a novel automatic system, based on Neural Networks (NN), for foot pathologies detection. In order to improve the efficiency of the neural network training algorithm, we propose the use of principal components analysis to reduce the number of inputs to the NN. The results obtained with this system demonstrate the feasibility of building automatic diagnosis systems based on the foot image. These systems are very valuable in remote areas and can be also used for massive first screening health campaigns.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::41cc0421721ba6011dee0dab3b499ab2 https://doi.org/10.1007/978-3-540-71629-7_13 Zobrazit plný text záznamu