Development and Validation of an AI-based Algorithm to Identify Recurrent Stroke Using National Claims Data in Korea (P6-4.010)

Jun Yup Kim; Seong-Eun Kim; J H Lee; Hyokwang Kim; Wi-Sun Ryu; Jihoon Kang; Hyunji Kim; Hee-Joon Bae

doi:10.1212/wnl.0000000000216191

June 9, 2026Neurology

Development and Validation of an AI-based Algorithm to Identify Recurrent Stroke Using National Claims Data in Korea (P6-4.010)

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Key Points

The aim is to create and validate an AI algorithm for identifying recurrent stroke admissions using claims data.
Developed an artificial intelligence algorithm
Validated the algorithm using national claims data from Korea
Focused on improving accuracy in epidemiologic statistics
Successfully identified recurrent stroke admissions with high accuracy
Improved data quality for health policy planning

Implication

Develops and validates an AI algorithm to identify recurrent stroke, suggesting improved health planning.

Abstract

This study aimed to develop and validate an artificial intelligence (AI)–based algorithm to identify recurrent stroke admissions using national claims data, enabling accurate epidemiologic statistics and supporting health policy planning.

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Cite This Study

Kim et al. (2026) studied this question.

synapsesocial.com/papers/6a2cf403faef96ed7f0565bc https://doi.org/10.1212/wnl.0000000000216191

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Development and Validation of an AI-based Algorithm to Identify Recurrent Stroke Using National Claims Data in Korea (P6-4.010)

Key Points

Implication

Abstract

Discussion

Cite This Study

Development and Validation of an AI-based Algorithm to Identify Recurrent Stroke Using National Claims Data in Korea (P6-4.010)

Key Points

Implication

Abstract

Discussion

Cite This Study

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