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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/9408
Ver los metadatos del registro completo
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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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article |
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publishedVersion |
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http://sedici.unlp.edu.ar/handle/10915/9408 |
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dc.language.none.fl_str_mv |
eng |
language |
eng |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc/3.0/ Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) |
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openAccess |
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http://creativecommons.org/licenses/by-nc/3.0/ Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) |
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application/pdf |
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