Non-invasive diagnosis of risk in dengue patients using bioelectrical impedance analysis and artificial neural network

This paper presents a new approach to diagnose and classify early risk in dengue patients using bioelectrical impedance analysis (BIA) and artificial neural network (ANN). A total of 223 healthy subjects and 207 hospitalized dengue patients were prospectively studied. The dengue risk severity criter...

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Veröffentlicht in:	Medical & biological engineering & computing 2010-11, Vol.48 (11), p.1141-1148
Hauptverfasser:	Ibrahim, F., Faisal, T., Mohamad Salim, M. I., Taib, M. N.
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Alanine Alanine transaminase Algorithms Artificial neural networks Aspartate aminotransferase Back propagation networks Bioelectricity Biomedical and Life Sciences Biomedical engineering Biomedical Engineering and Bioengineering Biomedicine Blood Body temperature Classification Computer Applications Dengue - diagnosis Dengue fever Diagnosis, Computer-Assisted - methods Disease control Early Diagnosis Electric Impedance Electrodes Engineering Fatalities Female Fever Health care Hematocrit Human Physiology Humans Imaging Impedance Learning theory Male Medical diagnosis Momentum Neural networks Neural Networks (Computer) Original Article Parameters Patients Patients rights Radiology Reactance Risk Risk Assessment Risk groups Statistical analysis Studies Transaminases Transfer functions Vector-borne diseases
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