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A Blockchain and Machine Learning based Framework for Efficient Health Insurance Management

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dc.contributor.author Chamola, Vinay
dc.date.accessioned 2023-03-17T07:11:17Z
dc.date.available 2023-03-17T07:11:17Z
dc.date.issued 2021-11
dc.identifier.uri https://dl.acm.org/doi/abs/10.1145/3485730.3493685
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9809
dc.description.abstract Having a health insurance is important for everybody, bearing in mind the increasing medical costs. Medical emergencies can have a severe financial and emotional impact. However, the current insurance system is very expensive and the claim settlement process is excessively lengthy, making it tedious. This results in policyholders not being able to successfully make a claim with their insurance company. In this paper, we focus on developing a fast and cost-effective framework based on blockchain technology and machine learning for the health insurance industry. Blockchain is capable of removing all third-party organisations by forming a smart contract, making the entire process more smooth, secure, and efficient. The contract settles the claim on documents submitted by the claimant. A ridge regression model is used for computing the premiums optimally, based on the total amount claimed under the current policy tenure, along with several other factors. A random forest classifier is applied for predicting the risk that helps in the computation of risk-rated premium rebate. en_US
dc.language.iso en en_US
dc.publisher ACM Digital Library en_US
dc.subject EEE en_US
dc.subject Blockchain en_US
dc.subject Machine learning (ML) en_US
dc.subject Health Insurance Management en_US
dc.title A Blockchain and Machine Learning based Framework for Efficient Health Insurance Management en_US
dc.type Article en_US


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