PMID- 25247174
OWN - NLM
STAT- MEDLINE
DCOM- 20150615
LR  - 20211021
IS  - 2314-6141 (Electronic)
IS  - 2314-6133 (Print)
VI  - 2014
DP  - 2014
TI  - Function formula oriented construction of Bayesian inference nets for diagnosis 
      of cardiovascular disease.
PG  - 376378
LID - 10.1155/2014/376378 [doi]
LID - 376378
AB  - An intelligent cardiovascular disease (CVD) diagnosis system using hemodynamic 
      parameters (HDPs) derived from sphygmogram (SPG) signal is presented to support 
      the emerging patient-centric healthcare models. To replicate clinical approach of 
      diagnosis through a staged decision process, the Bayesian inference nets (BIN) 
      are adapted. New approaches to construct a hierarchical multistage BIN using 
      defined function formulas and a method employing fuzzy logic (FL) technology to 
      quantify inference nodes with dynamic values of statistical parameters are 
      proposed. The suggested methodology is validated by constructing hierarchical 
      Bayesian fuzzy inference nets (HBFIN) to diagnose various heart pathologies from 
      the deduced HDPs. The preliminary diagnostic results show that the proposed 
      methodology has salient validity and effectiveness in the diagnosis of 
      cardiovascular disease.
FAU - Sekar, Booma Devi
AU  - Sekar BD
AD  - Department of ECE, Faculty of Science & Technology, University of Macau, Avenue 
      Padre Tomas Pereira S.J.S, Macau.
FAU - Dong, Mingchui
AU  - Dong M
AD  - Department of ECE, Faculty of Science & Technology, University of Macau, Avenue 
      Padre Tomas Pereira S.J.S, Macau.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20140827
PL  - United States
TA  - Biomed Res Int
JT  - BioMed research international
JID - 101600173
SB  - IM
MH  - Adolescent
MH  - Adult
MH  - Aged
MH  - Aged, 80 and over
MH  - Artificial Intelligence
MH  - *Bayes Theorem
MH  - Blood Pressure Determination/*methods
MH  - Cardiovascular Diseases/*diagnosis
MH  - Child, Preschool
MH  - Diagnosis, Computer-Assisted/*methods
MH  - Female
MH  - Humans
MH  - Infant
MH  - Infant, Newborn
MH  - Male
MH  - Middle Aged
MH  - *Neural Networks, Computer
MH  - Pattern Recognition, Automated/*methods
MH  - Reproducibility of Results
MH  - Sensitivity and Specificity
MH  - *Sphygmomanometers
PMC - PMC4163461
EDAT- 2014/09/24 06:00
MHDA- 2015/06/16 06:00
PMCR- 2014/08/27
CRDT- 2014/09/24 06:00
PHST- 2014/02/06 00:00 [received]
PHST- 2014/07/15 00:00 [revised]
PHST- 2014/07/31 00:00 [accepted]
PHST- 2014/09/24 06:00 [entrez]
PHST- 2014/09/24 06:00 [pubmed]
PHST- 2015/06/16 06:00 [medline]
PHST- 2014/08/27 00:00 [pmc-release]
AID - 10.1155/2014/376378 [doi]
PST - ppublish
SO  - Biomed Res Int. 2014;2014:376378. doi: 10.1155/2014/376378. Epub 2014 Aug 27.