• Title/Summary/Keyword: Health Insurance Review Assment

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The Prediction of Survival of Breast Cancer Patients Based on Machine Learning Using Health Insurance Claim Data (건강보험 청구 데이터를 활용한 머신러닝 기반유방암 환자의 생존 여부 예측)

  • Doeggyu Lee;Kyungkeun Byun;Hyungdong Lee;Sunhee Shin
    • Journal of Korea Society of Industrial Information Systems
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    • v.28 no.2
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    • pp.1-9
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    • 2023
  • Research using AI and big data is also being actively conducted in the health and medical fields such as disease diagnosis and treatment. Most of the existing research data used cohort data from research institutes or some patient data. In this paper, the difference in the prediction rate of survival and the factors affecting survival between breast cancer patients in their 40~50s and other age groups was revealed using health insurance review claim data held by the HIRA. As a result, the accuracy of predicting patients' survival was 0.93 on average in their 40~50s, higher than 0.86 in their 60~80s. In terms of that factor, the number of treatments was high for those in their 40~50s, and age was high for those in their 60~80s. Performance comparison with previous studies, the average precision was 0.90, which was higher than 0.81 of the existing paper. As a result of performance comparison by applied algorithm, the overall average precision of Decision Tree, Random Forest, and Gradient Boosting was 0.90, and the recall was 1.0, and the precision of multi-layer perceptrons was 0.89, and the recall was 1.0. I hope that more research will be conducted using machine learning automation(Auto ML) tools for non-professionals to enhance the use of the value for health insurance review claim data held by the HIRA.