Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/335653
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dc.date.accessioned2021-08-10T11:48:56Z-
dc.date.available2021-08-10T11:48:56Z-
dc.identifier.urihttp://hdl.handle.net/10603/335653-
dc.description.abstractAbstract newline newline newlineThe primary goal of the human being is to traverse the journey of life without peril. Here, This Research work is approaching quenching the risk of life from the perspective of advent technology in terms of Machine Learning. The term Machine Learning is got eulogized due to its pervasive nature and application. Here Machine learning nourished the prediction algorithm in the shadow of Data Mining in plausible means to quench the risk of life. This novel approach in the Data Mining system makes a prediction algorithm to reduce life risk due to the advent of data communication and machine learning. For monitoring of life risk, it uses a combination of the sensor into the dynamics of healthcare monitoring and guides possible remedial measures.These are being deployed for various applications and have huge research potential. However, owing to the multidisciplinary nature of this field, researchers have to face many technical hitches. This research work discusses the importance of Artificial Intelligence approaches to enable such Intelligent Communication Networks in the context of healthcare. This research work is organized around three major works: Analysis of conventional methodologies, proposing a systematic optimized generalized design approach for ubiquitous healthcare design, and a robust algorithm for classification of healthcare data and detection of disease. newline newline newline newline newline newline newline newline newline
dc.format.extentxviii,161p.
dc.languageEnglish
dc.relationp.141-160
dc.rightsuniversity
dc.titleDecision support system for healthcare in context of evolutionary computing techniques
dc.title.alternative
dc.creator.researcherNeelam sanjeev kumar
dc.subject.keywordHealthcare
dc.subject.keywordComputing techniques
dc.subject.keywordData Mining
dc.description.note
dc.contributor.guideNirmal Kumar P
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2020
dc.date.awarded2020
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File58.89 kBAdobe PDFView/Open
02_certificates.pdf355.96 kBAdobe PDFView/Open
03_vivaproceedings.pdf517.81 kBAdobe PDFView/Open
04_bonafidecertificate.pdf391.17 kBAdobe PDFView/Open
05_abstracts.pdf1.21 MBAdobe PDFView/Open
06_acknowledgements.pdf430.62 kBAdobe PDFView/Open
07_contents.pdf854.8 kBAdobe PDFView/Open
08_listoftables.pdf154.22 kBAdobe PDFView/Open
09_listoffigures.pdf430.63 kBAdobe PDFView/Open
10_listofabbreviations.pdf139.09 kBAdobe PDFView/Open
11_chapter1.pdf5 MBAdobe PDFView/Open
12_chapter2.pdf6.09 MBAdobe PDFView/Open
13_chapter3.pdf6.19 MBAdobe PDFView/Open
14_chapter4.pdf7.58 MBAdobe PDFView/Open
15_chapter5.pdf9.46 MBAdobe PDFView/Open
16_conclusion.pdf1.55 MBAdobe PDFView/Open
17_appendices.pdf757.38 kBAdobe PDFView/Open
18_references.pdf7.85 MBAdobe PDFView/Open
19_listofpublications.pdf189.56 kBAdobe PDFView/Open
80_recommendation.pdf1.61 MBAdobe PDFView/Open


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