머신러닝 알고리즘 기반의 의료비 예측 모델 개발

• 영문명: Development of Medical Cost Prediction Model Based on the Machine Learning Algorithm
• 발행기관: 한국인공지능학회
• 저자명: Han Bi KIM Dong Hoon HAN
• 간행물 정보: 『한국인공지능학회지』Vol.1 No.1, 11~16쪽, 전체 6쪽
• 주제분류: 복합학 > 과학기술학
• 파일형태: PDF
• 발행일자: 2023.06.30

국문 초록

Accurate hospital case modeling and prediction are crucial for efficient healthcare. In this study, we demonstrate the implementation of regression analysis methods in machine learning systems utilizing mathematical statics and machine learning techniques. The developed machine learning model includes Bayesian linear, artificial neural network, decision tree, decision forest, and linear regression analysis models. Through the application of these algorithms, corresponding regression models were constructed and analyzed. The results suggest the potential of leveraging machine learning systems for medical research. The experiment aimed to create an Azure Machine Learning Studio tool for the speedy evaluation of multiple regression models. The tool faciliates the comparision of 5 types of regression models in a unified experiment and presents assessment results with performance metrics. Evaluation of regression machine learning models highlighted the advantages of boosted decision tree regression, and decision forest regression in hospital case prediction. These findings could lay the groundwork for the deliberate development of new directions in medical data processing and decision making. Furthermore, potential avenues for future research may include exploring methods such as clustering, classification, and anomaly detection in healthcare systems.

목차

1. Introduction

2. Literature Review and Discussion

3. Body

4. Model Construction and Experiment

5. Results

6. Conclusion

References

키워드

Machine learning Algorithm Models Regression Prediction Azure Mchine Learning Studio R Error Accuracy Performance metrics Health care