Mechanism Analysis of High-Quality Development of Medical Insurance Supervision in the Context of Intelligent Management of Medical Record Information

Ying Han (), Chengyi Pu, Wenjing Fan, Hui Li and Xiaoli Song
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Ying Han: Beijing City University
Chengyi Pu: Central University of Finance and Economics
Wenjing Fan: Beijing City University
Hui Li: Beijing City University
Xiaoli Song: Beijing City University

A chapter in Proceedings of the 11th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2024), 2025, pp 212-218 from Springer

Abstract: Abstract China’s medical insurance supervision is facing new challenges, with hidden and complex medical violations leading to waste of funds, damage to patient interests, and misallocation of resources. The popularity of electronic medical systems has led to the storage of a large amount of medical information in the form of electronic medical records. However, the reliance of traditional natural language processing techniques on unlabeled data limits their effective application. Deep learning algorithms can effectively process unlabeled data through unsupervised learning, solving the problems of information dispersion and low utilization. Moreover, the intelligent medical insurance supervision technology based on deep learning improves the efficiency and safety of medical services through abnormal data detection and disease score payment.

Keywords: Deep Learning; DIP; Medical Insurance (search for similar items in EconPapers)
Date: 2025
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DOI: 10.2991/978-94-6463-946-9_27

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