Pattern recognition in medical images using neural networks

Autores
Lanzarini, Laura Cristina; De Giusti, Armando Eduardo
Año de publicación
2001
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The proposal of this research line is the search for alternatives to the resolution of complex problems where human knowledge should be apprehended in a general fashion. In particular, the activities developed so far can be included in the area of Medical Diagnosis, even though similar applications in other fields are not discarded. In general, one of the greatest problems of medical diagnosis is the subjectivity of the specialist. The experience of the professional greatly affects the final diagnosis. This is due to the fact that the result does not depend on a systematized solution, but on the interpretation of the patient´s answer. The solution to this kind of problems can be found in the area of Adaptive Pattern Recognition, where the solution rests on the easiness with which the systems adapts to the information available, in this case coming from the patient. In this sense, neural networks are extremely useful, since they are not only capable of learning with the aid of an expert, but they can also make generalizations based on the information from the input data, thus showing relations that are a priori of a complex nature.
Facultad de Informática
Materia
Ciencias Informáticas
neural networks; adaptive pattern recognition; medical diagnosis
Redes neuronales
Reconocimiento de patrones
Diagnosis
Medicina
Procesamiento de imagen
Informática
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/9408

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network_name_str SEDICI (UNLP)
spelling Pattern recognition in medical images using neural networksLanzarini, Laura CristinaDe Giusti, Armando EduardoCiencias Informáticasneural networks; adaptive pattern recognition; medical diagnosisRedes neuronalesReconocimiento de patronesDiagnosisMedicinaProcesamiento de imagenInformáticaThe proposal of this research line is the search for alternatives to the resolution of complex problems where human knowledge should be apprehended in a general fashion. In particular, the activities developed so far can be included in the area of Medical Diagnosis, even though similar applications in other fields are not discarded. In general, one of the greatest problems of medical diagnosis is the subjectivity of the specialist. The experience of the professional greatly affects the final diagnosis. This is due to the fact that the result does not depend on a systematized solution, but on the interpretation of the patient´s answer. The solution to this kind of problems can be found in the area of Adaptive Pattern Recognition, where the solution rests on the easiness with which the systems adapts to the information available, in this case coming from the patient. In this sense, neural networks are extremely useful, since they are not only capable of learning with the aid of an expert, but they can also make generalizations based on the information from the input data, thus showing relations that are a priori of a complex nature.Facultad de Informática2001info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/9408enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/pap41.pdfinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/3.0/Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:23:30Zoai:sedici.unlp.edu.ar:10915/9408Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:23:30.72SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Pattern recognition in medical images using neural networks
title Pattern recognition in medical images using neural networks
spellingShingle Pattern recognition in medical images using neural networks
Lanzarini, Laura Cristina
Ciencias Informáticas
neural networks; adaptive pattern recognition; medical diagnosis
Redes neuronales
Reconocimiento de patrones
Diagnosis
Medicina
Procesamiento de imagen
Informática
title_short Pattern recognition in medical images using neural networks
title_full Pattern recognition in medical images using neural networks
title_fullStr Pattern recognition in medical images using neural networks
title_full_unstemmed Pattern recognition in medical images using neural networks
title_sort Pattern recognition in medical images using neural networks
dc.creator.none.fl_str_mv Lanzarini, Laura Cristina
De Giusti, Armando Eduardo
author Lanzarini, Laura Cristina
author_facet Lanzarini, Laura Cristina
De Giusti, Armando Eduardo
author_role author
author2 De Giusti, Armando Eduardo
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
neural networks; adaptive pattern recognition; medical diagnosis
Redes neuronales
Reconocimiento de patrones
Diagnosis
Medicina
Procesamiento de imagen
Informática
topic Ciencias Informáticas
neural networks; adaptive pattern recognition; medical diagnosis
Redes neuronales
Reconocimiento de patrones
Diagnosis
Medicina
Procesamiento de imagen
Informática
dc.description.none.fl_txt_mv The proposal of this research line is the search for alternatives to the resolution of complex problems where human knowledge should be apprehended in a general fashion. In particular, the activities developed so far can be included in the area of Medical Diagnosis, even though similar applications in other fields are not discarded. In general, one of the greatest problems of medical diagnosis is the subjectivity of the specialist. The experience of the professional greatly affects the final diagnosis. This is due to the fact that the result does not depend on a systematized solution, but on the interpretation of the patient´s answer. The solution to this kind of problems can be found in the area of Adaptive Pattern Recognition, where the solution rests on the easiness with which the systems adapts to the information available, in this case coming from the patient. In this sense, neural networks are extremely useful, since they are not only capable of learning with the aid of an expert, but they can also make generalizations based on the information from the input data, thus showing relations that are a priori of a complex nature.
Facultad de Informática
description The proposal of this research line is the search for alternatives to the resolution of complex problems where human knowledge should be apprehended in a general fashion. In particular, the activities developed so far can be included in the area of Medical Diagnosis, even though similar applications in other fields are not discarded. In general, one of the greatest problems of medical diagnosis is the subjectivity of the specialist. The experience of the professional greatly affects the final diagnosis. This is due to the fact that the result does not depend on a systematized solution, but on the interpretation of the patient´s answer. The solution to this kind of problems can be found in the area of Adaptive Pattern Recognition, where the solution rests on the easiness with which the systems adapts to the information available, in this case coming from the patient. In this sense, neural networks are extremely useful, since they are not only capable of learning with the aid of an expert, but they can also make generalizations based on the information from the input data, thus showing relations that are a priori of a complex nature.
publishDate 2001
dc.date.none.fl_str_mv 2001
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info:eu-repo/semantics/publishedVersion
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Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
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