An adaptive and interpretable case grouping framework for healthcare payment systems

20260 citationsJournal Articlegold Open Access

Authors

Gaocheng Cai · Shenzhen University

Yuda Wang · Shenzhen University

Ning Liu · Shenzhen University

Mengjie Wan · Shenzhen University

Zhimei Zeng · Shenzhen University

Ben Niu · Shenzhen University

Abstract

The proposed framework offers a theoretically sound and practically feasible method for case grouping in the medical insurance payment systems. Its flexibility and scalability support the development of more accurate and equitable reimbursement schemes.

Topics & Keywords

Artificial Intelligence in Healthcare Financial Distress and Bankruptcy Prediction Imbalanced Data Classification Techniques

Publication Details

Published in: International Journal for Equity in Health

DOI: 10.1186/s12939-026-02813-2

Field-Weighted Citation Impact: 0.00

Command Palette

An adaptive and interpretable case grouping framework for healthcare payment systems

Authors

Abstract

Topics & Keywords

Publication Details