Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)

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Analysis and Prediction of Health Insurance Cost Using Machine Learning Approaches

Authors
Dileep Kumar Kadali1, *, M. Lakshmi Narayana2, V. S. N. Murthy1, Srinivasa Rao Dangeti1, Yugandhar Bokka1, Samatham Chandra Sekhara Rao1
1Shri Vishnu Engineering College for Women, Bhimavaram, AP, India
2S.R.K.R Engineering College, Bhimavaram, AP, India
*Corresponding author. Email: dileepkumarkadali@gmail.com
Corresponding Author
Dileep Kumar Kadali
Available Online 30 July 2024.
DOI
10.2991/978-94-6463-471-6_55How to use a DOI?
Keywords
Machine Learning; Estimation Model; Random Forest; Gradient Boosting etc.
Abstract

The intensifying cost of healthcare needs tools for up-to-date insurance ranges. Machine Learning approaches for predicting individual healthcare insurance costs are analyzed with the help of patient records, and a personalized cost estimation model empowers individuals, particularly in rural areas, to navigate complex insurance options. Unlike existing solutions, our model does not predict specific company costs but provides a personalized cost range. To overcome to proposed this paper focuses on affordability and informed decision-making and addresses challenges like limited health literacy and lack of awareness of government-provided schemes. The machine learning algorithms are Gradient Boosting and Random Forest to achieve high accuracy enabling all individuals, especially those in underserved communities, to make informed healthcare investment decisions.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
Series
Advances in Computer Science Research
Publication Date
30 July 2024
ISBN
978-94-6463-471-6
ISSN
2352-538X
DOI
10.2991/978-94-6463-471-6_55How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Dileep Kumar Kadali
AU  - M. Lakshmi Narayana
AU  - V. S. N. Murthy
AU  - Srinivasa Rao Dangeti
AU  - Yugandhar Bokka
AU  - Samatham Chandra Sekhara Rao
PY  - 2024
DA  - 2024/07/30
TI  - Analysis and Prediction of Health Insurance Cost Using Machine Learning Approaches
BT  - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
PB  - Atlantis Press
SP  - 569
EP  - 577
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-471-6_55
DO  - 10.2991/978-94-6463-471-6_55
ID  - Kadali2024
ER  -