Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/12894
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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.date.accessioned2020-02-03T03:27:38Z-
dc.date.available2020-02-03T03:27:38Z-
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.language.isoenen_US
dc.titleMachine learning for healthcare diagnosticsen_US
dc.typeArticleen_US
dc.identifier.doi10.35940/ijeat.F1304.0886S219-
item.fulltextWith Fulltext-
item.grantfulltextopen-
Appears in Collections:UNITEN Scholarly Publication
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