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Application of Support Vector Machines (SVM) for clinical diagnosis of Parkinson's Disease and Essential Tremor

Authors: González, Roberto; Barrientos, Antonio; Toapanta, Marcelo; Cerro, Jaime del;

Application of Support Vector Machines (SVM) for clinical diagnosis of Parkinson's Disease and Essential Tremor

Abstract

Los enfermos de Párkinson (EP) y de temblor esencial (TE) suponen un porcentaje importante de la casuística clínica en los trastornos del movimiento, que impiden a los sujetos afectados el llevar una vida normal, produciendo discapacidad física y una no menos importante exclusión social en muchos de los casos. Las vías de tratamiento son dispares, de ahí que sea crítico acertar con precisión en el diagnóstico en las etapas iniciales de la enfermedad. Hasta la actualidad, los profesionales y expertos en medicina, utilizan unas escalas cualitativas para diferenciar la patología y su grado de afectación. Dichas escalas también se utilizan para efectuar un seguimiento clínico y registrar la historia del paciente. En este trabajo se propone la utilización de clasificadores binarios centrados en las Máquinas de Soporte Vectorial (SVM) para obtener un diagnóstico diferencial entre las dos patologías de temblor mencionadas. (CC BY-NC-ND 4.0).

Este trabajo ha sido posible gracias a las pruebas que se realizaron durante largos periodos de tiempo en el Hospital Ramón y Cajal y en el Hospital de la Princesa, ambos de Madrid. Especial mención a los responsables e integrantes de los servicios de neurofisiología y neurocirugía del Hospital Ramón y Cajal con los que compartimos muchas horas de trabajo y dedicación. También hacer mención al Centro de Referencia Estatal de Autonomía Personal y Ayudas Técnicas (CEAPAT), organismo que financió el sistema DIMETER, herramienta fundamental cuyo desarrollo y utilización nos ha permitido poder llegar a las conclusiones que aquí exponemos tras un largo periodo de análisis, procesamiento y explotación de las pruebas realizadas. También agradecer a todos las personas que directa o indirectamente colaboraron en el proyecto DIMETER.

Parkinson's Disease (PD) and Essential Tremor (ET) patients represent a significant percentage of the clinical cases in movement disorders pathologies, which prevents to the affected people leading a normal life. A physical disability results and important social exclusion in many cases are produced. The treatment methods are very differents, so it is critical hitting with the diagnosis in the early stages of these diseases. Until today, professionals and experts in medicine, use qualitative scales to differentiate pathology cases and its level of affectation. These scales are used to follow up clinically and register the patient's history. This work proposes the use of binary classifiers focused on the Vector Support Machines (SVM) to obtain a differential diagnosis between the essential tremor and Parkinson’s disease.

Peer Reviewed

Keywords

clasificación Párkinson-Esencial, medida objetiva del temblor, Ayuda al diagnóstico, extracción de características, análisis de patrones, clasificadores binarios, diagnóstico médico.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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