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Developing a biotech scheme using fuzzy logic model to predict occurrence of diseases using person's functional state
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2020
Year
EngineeringSystem MedicineDiagnosisDisease ClassificationFuzzy Risk AnalysisHeart Disease PredictionHealth Monitoring (Structural Health Monitoring)Health Monitoring (Biomedical Engineering)Computational MedicineFuzzy Logic ModelMedical Expert SystemClinical DiagnosisBiostatisticsMonitoring Stress IndicatorsPublic HealthDisease DiagnosisFuzzy LogicCardiovascular EpidemiologyHealth PolicyDisease Risk AssessmentRiskCardiovascular ReactivityDecision Support SystemsMedical Decision AnalysisEpidemiologyBiotech SchemeFunctional StateCardiovascular DiseaseHealth MonitoringHealth Informatics
This research focuses on the evaluation of risk of cardiovascular diseases in persons at various functional states using monitoring stress indicators and developing fuzzy logic model. The model classifies responses in four classes. The physical records of 400 workers were analysed (100 persons for each of four classes). Risk of cardiovascular disease is evaluated using two groups of several characteristics: (1) the subjective test questionnaires and indicators describing the human attention, (2) the level of the functional state can be used as indicator in forecasting and diagnosis, which can be measured by psychological tests to determine the state of human attention. The accuracy of prediction and early detection of cardiovascular and nervous system diseases were estimated in a similar way and it was found out that the use of indicators characterising a person's functional state system improves the quality of classification for these diseases by 10 ± 2% for prediction and diagnostic decision rules.