Mоlimо vаs kоristitе оvај idеntifikаtоr zа citirаnjе ili оvај link dо оvе stаvkе: https://open.uns.ac.rs/handle/123456789/4276
Pоljе DC-аVrеdnоstЈеzik
dc.contributor.authorAleksandar Kupusinacen_US
dc.contributor.authorEdita Stokićen_US
dc.contributor.authorEnes Sukićen_US
dc.contributor.authorOlivera Rankoven_US
dc.contributor.authorAndrea Katićen_US
dc.date.accessioned2019-09-23T10:33:06Z-
dc.date.available2019-09-23T10:33:06Z-
dc.date.issued2017-01-01-
dc.identifier.issn1485598en_US
dc.identifier.urihttps://open.uns.ac.rs/handle/123456789/4276-
dc.description.abstract© 2016, Springer Science+Business Media New York. Although body mass index (BMI) and body fat percentage (BF%) are well known as indicators of nutritional status, there are insuficient data whether the relationship between them is linear or not. There are appropriate linear and quadratic formulas that are available to predict BF% from age, gender and BMI. On the other hand, our previous research has shown that artificial neural network (ANN) is a more accurate method for that. The aim of this study is to analyze relationship between BMI and BF% by using ANN and big dataset (3058 persons). Our results show that this relationship is rather quadratic than linear for both gender and all age groups. Comparing genders, quadratic relathionship is more pronounced in women, while linear relationship is more pronounced in men. Additionaly, our results show that quadratic relationship is more pronounced in old than in young and middle-age men and it is slightly more pronounced in young and middle-age than in old women.en_US
dc.language.isoenen_US
dc.relation.ispartofJournal of Medical Systemsen_US
dc.subjectArtificial neural networksen_US
dc.subjectBig dataen_US
dc.subjectBodymass indexen_US
dc.subjectBody fat percentageen_US
dc.subjectObesityen_US
dc.titleWhat kind of Relationship is Between Body Mass Index and Body Fat Percentage?en_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.doi10.1007/s10916-016-0636-9-
dc.identifier.pmid41-
dc.identifier.scopus2-s2.0-84994884969-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84994884969-
dc.description.versionPublisheden_US
dc.relation.issue1en_US
dc.relation.volume41en_US
item.grantfulltextnone-
item.fulltextNo Fulltext-
crisitem.author.deptFakultet tehničkih nauka, Departman za računarstvo i automatiku-
crisitem.author.deptMedicinski fakultet, Katedra za internu medicinu-
crisitem.author.parentorgFakultet tehničkih nauka-
crisitem.author.parentorgMedicinski fakultet-
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