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http://hdl.handle.net/10603/335653
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DC Field | Value | Language |
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dc.coverage.spatial | ||
dc.date.accessioned | 2021-08-10T11:48:56Z | - |
dc.date.available | 2021-08-10T11:48:56Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/335653 | - |
dc.description.abstract | Abstract 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.extent | xviii,161p. | |
dc.language | English | |
dc.relation | p.141-160 | |
dc.rights | university | |
dc.title | Decision support system for healthcare in context of evolutionary computing techniques | |
dc.title.alternative | ||
dc.creator.researcher | Neelam sanjeev kumar | |
dc.subject.keyword | Healthcare | |
dc.subject.keyword | Computing techniques | |
dc.subject.keyword | Data Mining | |
dc.description.note | ||
dc.contributor.guide | Nirmal Kumar P | |
dc.publisher.place | Chennai | |
dc.publisher.university | Anna University | |
dc.publisher.institution | Faculty of Information and Communication Engineering | |
dc.date.registered | ||
dc.date.completed | 2020 | |
dc.date.awarded | 2020 | |
dc.format.dimensions | 21cm | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 58.89 kB | Adobe PDF | View/Open |
02_certificates.pdf | 355.96 kB | Adobe PDF | View/Open | |
03_vivaproceedings.pdf | 517.81 kB | Adobe PDF | View/Open | |
04_bonafidecertificate.pdf | 391.17 kB | Adobe PDF | View/Open | |
05_abstracts.pdf | 1.21 MB | Adobe PDF | View/Open | |
06_acknowledgements.pdf | 430.62 kB | Adobe PDF | View/Open | |
07_contents.pdf | 854.8 kB | Adobe PDF | View/Open | |
08_listoftables.pdf | 154.22 kB | Adobe PDF | View/Open | |
09_listoffigures.pdf | 430.63 kB | Adobe PDF | View/Open | |
10_listofabbreviations.pdf | 139.09 kB | Adobe PDF | View/Open | |
11_chapter1.pdf | 5 MB | Adobe PDF | View/Open | |
12_chapter2.pdf | 6.09 MB | Adobe PDF | View/Open | |
13_chapter3.pdf | 6.19 MB | Adobe PDF | View/Open | |
14_chapter4.pdf | 7.58 MB | Adobe PDF | View/Open | |
15_chapter5.pdf | 9.46 MB | Adobe PDF | View/Open | |
16_conclusion.pdf | 1.55 MB | Adobe PDF | View/Open | |
17_appendices.pdf | 757.38 kB | Adobe PDF | View/Open | |
18_references.pdf | 7.85 MB | Adobe PDF | View/Open | |
19_listofpublications.pdf | 189.56 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 1.61 MB | Adobe PDF | View/Open |
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