Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/527801
Title: | A secure health care management and service retrieval for society over apache spark hadoop environment |
Researcher: | Vimala Ithayan, J |
Guide(s): | Sundar, C and Babu |
Keywords: | Big Data Engineering Engineering and Technology Engineering Electrical and Electronic Hadoop Health care management |
University: | Anna University |
Completed Date: | 2022 |
Abstract: | The term Big Data is a key technology that describes the sheer volume newlineof data. These are highly underutilized by healthcare organizations. In most newlinecommon, the wealth of customer information can be used by healthcare sectors to newlineconstruct and stand-in customer and patient relationships with the aim of newlineoptimizing marketing, clinical, and business outcomes. Big Data technologies newlinehave been widely used for many successful applications in health sciences newlineespecially, in biomedicine. E.g. the data from social networks and search engines newlinecan help to collect people s reactions and monitor the conditions of epidemic newlinediseases. For efficient data management and analysis, a huge volume of health newlinedata is transmitted to third parties for data analysis and mining. In such cases, it is newlinedifficult to directly analyse the large volume of raw health data. Various big data newlinehealthcare applications including the recommendation systems in healthcare, newlineInternet-based epidemic surveillance, sensor-based health conditions, food safety newlinemonitoring, etc. Predictive analytics has been widely utilized to minimize the degree of newlineuncertainty like preventable readmissions and enables domain experts to finalize newlinebetter decisions. Furthermore, it supports preventive care and it allows healthcare newlineorganizations to estimate their current service situations to assist them to newlineunderstand the complex structure of the clinical data. Typically, the amount of health data increases by their size, computational complexity, and speed. A traditional healthcare system often requires the delivery of medical data to the large storage system, which is newlinecomprised of patient s sensitive information and causes communication overhead. newlineBasically, medical sharing is a serious threat and also a challenging issue. For newlinethese reasons, a range of big data analytical approaches such as Machine Learning newlineand Text Mining are often required for organizing huge amounts of data. This newlineresearch, focus on two big data analytics strategies: Data Retrieval and Data newline Management over Hadoop Distributed File System (HDFS). newline newline |
Pagination: | xvii,112p. |
URI: | http://hdl.handle.net/10603/527801 |
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 | 24.54 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 2.25 MB | Adobe PDF | View/Open | |
03_content.pdf | 86.72 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 78.64 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 478.64 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 376.21 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 256.76 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 641.64 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 403.5 kB | Adobe PDF | View/Open | |
10_annexures.pdf | 113.55 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 77 kB | Adobe PDF | View/Open |
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