Chan, Nicholas Kin Whai and Lee, Angela Siew Hoong * and Zuraini Zainol, (2021) Predicting employee health risks using classification ensemble model. In: Fifth International Conference on Information Retrieval and Knowledge Management (CAMP), 15-16 June 2021, Kuala Lumpur, Malaysia.
Full text not available from this repository.Abstract
Our planet is known as a digital earth, circulating around data. Growth in data is exponential, leading to an elevated interest in Big Data Analytics, to collect, store, process, analyze and visualize unparalleled amount of data. Modern information driven society will continue to be shaped by big data, where there will be potential to extract meaningful insights and hidden patterns impacting businesses in unforeseen measures. Most employers in Malaysia provide medical benefits which includes general medical costs to hospitalization benefits and insurance coverages; with these data and information stored by the HR (Human Resource), leading to a potential to analyze and identify patterns in historical claims - these insights would lead to improved decision making to better understand employee population health and the usage of the premium coverage. In predictive analysis, common techniques applied are Decision Tree and Regression. Therefore, the aim of this research is to propose a conceptual prediction model to better understand the patterns present in the employee healthcare data while predicting if an employee would be at any health risks to understand the population health and the usage of premium coverage provided by the employer. Additionally, to apply an ensemble method called Stacking, where multiple predictive models will be combined to perform a prediction. An ensemble model will present the opportunity to build a more robust and accurate model which could be applied across various industries instead of being industry specific.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Big Data Analytics; Healthcare; Ensemble Model; Stacking Model; Predictive Analysis; Decision Tree |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Others > Non Sunway Academics Sunway University > School of Engineering and Technology [formerly School of Science and Technology until 2020] > Dept. Computing and Information Systems |
| Depositing User: | Dr Janaki Sinnasamy |
| Related URLs: | |
| Date Deposited: | 07 Oct 2021 01:18 |
| Last Modified: | 07 Oct 2021 01:18 |
| URI: | http://eprints.sunway.edu.my/id/eprint/1858 |
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