Publication:
Machine learning for healthcare diagnostics

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dc.citedby1
dc.contributor.authorSutabri T.en_US
dc.contributor.authorPandi Selvam R.en_US
dc.contributor.authorShankar K.en_US
dc.contributor.authorNguyen P.T.en_US
dc.contributor.authorHashim W.en_US
dc.contributor.authorMaseleno A.en_US
dc.contributor.authorid57200216597en_US
dc.contributor.authorid57196346443en_US
dc.contributor.authorid56884031900en_US
dc.contributor.authorid57216386109en_US
dc.contributor.authorid11440260100en_US
dc.contributor.authorid55354910900en_US
dc.date.accessioned2023-05-29T07:24:12Z
dc.date.available2023-05-29T07:24:12Z
dc.date.issued2019
dc.description.abstractPresently machine learning and artificial intelligence is playing one of the most important role in diagnose many genetic and non genetic disease. So that the rapid inventions in machine learning can save thousands of life�s as it can diagnose the early stage of many serious diseases. In this research the datasets for such diseases is studied and it will be analyzed that how such deep machine learning will impact to a human life. The problem with such methodology is that it is not possible to get accurate results in the initial stage of research. The reason is every human have different immunity power and stamina. There are many diagnostics center who are fully dependent on the equipments which are fully based on machine learning. In order to boost this process it is necessary to collect the real time patient�s data from different hospitals, states and countries. So that it will be beneficial for world wide. � BEIESP.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.35940/ijeat.F1304.0886S219
dc.identifier.epage1001
dc.identifier.issue6 Special Issue 2
dc.identifier.scopus2-s2.0-85073718245
dc.identifier.spage999
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85073718245&doi=10.35940%2fijeat.F1304.0886S219&partnerID=40&md5=50341930020ce12ba69cdbe10246517f
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24525
dc.identifier.volume8
dc.publisherBlue Eyes Intelligence Engineering and Sciences Publicationen_US
dc.relation.ispartofAll Open Access, Bronze
dc.sourceScopus
dc.sourcetitleInternational Journal of Engineering and Advanced Technology
dc.titleMachine learning for healthcare diagnosticsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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