2014 · 12 citations · 5 references
ComputingBiomedical EngineeringHealth InformaticsBiomedical Signal ProcessingClinical Decision SupportMachine LearningCardiac Signal ProcessingDimensionality ReductionElectrocardiogram AnalysisElectrocardiogram InterpretationElectrocardiographyHealthcare AnalyticsCardiac Feature ExtractionEcg Feature ExtractionEcg Signal PreprocessingElectrocardiogram Feature ExtractionFilteringMachine Learning For Health MonitoringMachine Learning For HealthcareRadial Basis Function Networks
The main challenge of big data processing includes the extraction of relevant information, from a high dimensionality of a wide variety of medical data by enabling analysis, discovery and interpretation. These data are a useful tool for helping to understand disease and to formulate predictive models in different areas and support different tasks, such as triage, evaluation of treatment, and monitoring. In this paper, a case study based on a predictive model using the radial basis function neural network (RBFNN) combined with a filtering technique aiming the estimation of electrocardiogram (ECG) waveform is presented. The proposed method revealed it suitability to support health care professionals on clinical decisions and practices.
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