Cargando…
Fuzzy logic based risk assessment system giving individualized advice for metabolic syndrome and fatal cardiovascular diseases
In 2005, global cardiovascular diseases caused 30% of deaths in Europe, which is 46% of total deaths for all death groups. Today, according to the International Adult Diabetes Federation, 20% to 25% of the adult population in the world has Metabolic Syndrome. Turkish Statistical Institute claims tha...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
IOS Press
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598019/ https://www.ncbi.nlm.nih.gov/pubmed/31045527 http://dx.doi.org/10.3233/THC-199007 |
_version_ | 1783430687082151936 |
---|---|
author | Korkmaz, Hayriye Canayaz, Emre Birtane, Sibel Altıkardeş, Aysun |
author_facet | Korkmaz, Hayriye Canayaz, Emre Birtane, Sibel Altıkardeş, Aysun |
author_sort | Korkmaz, Hayriye |
collection | PubMed |
description | In 2005, global cardiovascular diseases caused 30% of deaths in Europe, which is 46% of total deaths for all death groups. Today, according to the International Adult Diabetes Federation, 20% to 25% of the adult population in the world has Metabolic Syndrome. Turkish Statistical Institute claims that in Turkey 408782 people died of circulatory system diseases in 2016 and it is expected that numbers will dramatically increase. In 2003, total worldwide healthcare budget of Diabetes Mellitus was up to 64.9 billion International Dollars with the continuing rise in prevalence, it is expected that total costs will increase to 396 billion International Dollars by 2025. The main purpose of this study was to present a clinical decision support system that calculates Metabolic Syndrome existence and evaluate HeartScore risk level for Turkish population. The second objective was to create a detailed personal report about individual’s risk level of Metabolic Syndrome and HeartScore and give advice to him/her to reduce it. The fuzzy logic risk assessment system (FLRAS) was formed in LabVIEW graphical development platform according to International Diabetes Federation and European Heart Journal’s criteria. Mamdani type fuzzy logic sets were identified for each input variable and membership functions were assigned depending on the magnitude of the input limits. System’s performance was tested on 96 (72 females, 24 males) patient data. Results show that the proposed system was able to evaluate the Metabolic Syndrome risk with 0.9285 specificity, 0.92708 accuracy and 0.925 sensitivity. |
format | Online Article Text |
id | pubmed-6598019 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | IOS Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-65980192019-07-01 Fuzzy logic based risk assessment system giving individualized advice for metabolic syndrome and fatal cardiovascular diseases Korkmaz, Hayriye Canayaz, Emre Birtane, Sibel Altıkardeş, Aysun Technol Health Care Research Article In 2005, global cardiovascular diseases caused 30% of deaths in Europe, which is 46% of total deaths for all death groups. Today, according to the International Adult Diabetes Federation, 20% to 25% of the adult population in the world has Metabolic Syndrome. Turkish Statistical Institute claims that in Turkey 408782 people died of circulatory system diseases in 2016 and it is expected that numbers will dramatically increase. In 2003, total worldwide healthcare budget of Diabetes Mellitus was up to 64.9 billion International Dollars with the continuing rise in prevalence, it is expected that total costs will increase to 396 billion International Dollars by 2025. The main purpose of this study was to present a clinical decision support system that calculates Metabolic Syndrome existence and evaluate HeartScore risk level for Turkish population. The second objective was to create a detailed personal report about individual’s risk level of Metabolic Syndrome and HeartScore and give advice to him/her to reduce it. The fuzzy logic risk assessment system (FLRAS) was formed in LabVIEW graphical development platform according to International Diabetes Federation and European Heart Journal’s criteria. Mamdani type fuzzy logic sets were identified for each input variable and membership functions were assigned depending on the magnitude of the input limits. System’s performance was tested on 96 (72 females, 24 males) patient data. Results show that the proposed system was able to evaluate the Metabolic Syndrome risk with 0.9285 specificity, 0.92708 accuracy and 0.925 sensitivity. IOS Press 2019-06-18 /pmc/articles/PMC6598019/ /pubmed/31045527 http://dx.doi.org/10.3233/THC-199007 Text en © 2019 – IOS Press and the authors. All rights reserved https://creativecommons.org/licenses/by-nc/4.0/ This article is published online with Open Access and distributed under the terms of the Creative Commons Attribution Non-Commercial License (CC BY-NC 4.0). |
spellingShingle | Research Article Korkmaz, Hayriye Canayaz, Emre Birtane, Sibel Altıkardeş, Aysun Fuzzy logic based risk assessment system giving individualized advice for metabolic syndrome and fatal cardiovascular diseases |
title | Fuzzy logic based risk assessment system giving individualized advice for metabolic syndrome and fatal cardiovascular diseases |
title_full | Fuzzy logic based risk assessment system giving individualized advice for metabolic syndrome and fatal cardiovascular diseases |
title_fullStr | Fuzzy logic based risk assessment system giving individualized advice for metabolic syndrome and fatal cardiovascular diseases |
title_full_unstemmed | Fuzzy logic based risk assessment system giving individualized advice for metabolic syndrome and fatal cardiovascular diseases |
title_short | Fuzzy logic based risk assessment system giving individualized advice for metabolic syndrome and fatal cardiovascular diseases |
title_sort | fuzzy logic based risk assessment system giving individualized advice for metabolic syndrome and fatal cardiovascular diseases |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598019/ https://www.ncbi.nlm.nih.gov/pubmed/31045527 http://dx.doi.org/10.3233/THC-199007 |
work_keys_str_mv | AT korkmazhayriye fuzzylogicbasedriskassessmentsystemgivingindividualizedadviceformetabolicsyndromeandfatalcardiovasculardiseases AT canayazemre fuzzylogicbasedriskassessmentsystemgivingindividualizedadviceformetabolicsyndromeandfatalcardiovasculardiseases AT birtanesibel fuzzylogicbasedriskassessmentsystemgivingindividualizedadviceformetabolicsyndromeandfatalcardiovasculardiseases AT altıkardesaysun fuzzylogicbasedriskassessmentsystemgivingindividualizedadviceformetabolicsyndromeandfatalcardiovasculardiseases |