Non-invasive diagnosis of risk in dengue patients using bioelectrical impedance analysis and artificial neural network.
about
Analysis of significant factors for dengue fever incidence predictionMorbidity Rate Prediction of Dengue Hemorrhagic Fever (DHF) Using the Support Vector Machine and the Aedes aegypti Infection Rate in Similar Climates and Geographical Areas.The application of biomedical engineering techniques to the diagnosis and management of tropical diseases: a review.Mathematical modelling and a systems science approach to describe the role of cytokines in the evolution of severe dengueBioimpedance Vector Analysis in Diagnosing Severe and Non-Severe Dengue Patients.
P2860
Non-invasive diagnosis of risk in dengue patients using bioelectrical impedance analysis and artificial neural network.
description
2010 nî lūn-bûn
@nan
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
2010年论文
@zh
2010年论文
@zh-cn
name
Non-invasive diagnosis of risk ...... and artificial neural network.
@en
type
label
Non-invasive diagnosis of risk ...... and artificial neural network.
@en
prefLabel
Non-invasive diagnosis of risk ...... and artificial neural network.
@en
P50
P1476
Non-invasive diagnosis of risk ...... and artificial neural network
@en
P2093
P304
P356
10.1007/S11517-010-0669-Z
P577
2010-08-04T00:00:00Z