Computer Aided Detection System for Prediction of the Malaise during Hemodialysis.
Comput Math Methods Med
; 2016: 8748156, 2016.
Article
en En
| MEDLINE
| ID: mdl-27042200
ABSTRACT
Monitoring of dialysis sessions is crucial as different stress factors can yield suffering or critical situations. Specialized personnel is usually required for the administration of this medical treatment; nevertheless, subjects whose clinical status can be considered stable require different monitoring strategies when compared with subjects with critical clinical conditions. In this case domiciliary treatment or monitoring can substantially improve the quality of life of patients undergoing dialysis. In this work, we present a Computer Aided Detection (CAD) system for the telemonitoring of patients' clinical parameters. The CAD was mainly designed to predict the insurgence of critical events; it consisted of two Random Forest (RF) classifiers the first one (RF1) predicting the onset of any malaise one hour after the treatment start and the second one (RF2) again two hours later. The developed system shows an accurate classification performance in terms of both sensitivity and specificity. The specificity in the identification of nonsymptomatic sessions and the sensitivity in the identification of symptomatic sessions for RF2 are equal to 86.60% and 71.40%, respectively, thus suggesting the CAD as an effective tool to support expert nephrologists in telemonitoring the patients.
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Diagnóstico por Computador
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Diálisis Renal
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Mareo
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Fallo Renal Crónico
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Calambre Muscular
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Náusea
Tipo de estudio:
Diagnostic_studies
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Etiology_studies
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Prognostic_studies
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Risk_factors_studies
Límite:
Adult
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Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Comput Math Methods Med
Asunto de la revista:
INFORMATICA MEDICA
Año:
2016
Tipo del documento:
Article
País de afiliación:
Italia