Construction and Application of a Pediatric Kawasaki Disease Specialized Platform Based on Multimodal Data

Corresponding author: QI Guoqiang, qiguoqiang@zju.edu.cn

DOI: 10.12201/bmr.202511.00056

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  Abstract: Purpose/Significance:To address challenges in the clinical management of Kawasaki disease (KD) in children, such as difficulties in early diagnosis, non-standardized treatment, and underutilization of data, this study aimed to construct a specialized KD platform based on multimodal data to integrate and manage dispersed medical data, supporting optimized clinical diagnosis/treatment and scientific research.Method/Process: Based on the diagnostic and treatment data of KD children from the Childrens Hospital Zhejiang University School of Medicine (2018-2024), multi-source heterogeneous data were aggregated through ETL technology. Data were cleaned, standardized, and structured using Natural Language Processing (NLP), machine vision, and data governance techniques to establish a specialized database centered around the Enterprise Master Patient Index (EMPI). The platform integrated functional modules for patient management, intelligent search, research project, and follow-up management, and employed machine learning algorithms to support data analysis.Result/Conclusion: A specialized KD database was successfully constructed, containing 10,689 confirmed cases and covering 300 data items across 18 modules. The platform achieved effective integration and quality control of multimodal data, providing efficient case retrieval, cohort building, and research analysis capabilities, significantly improving data utilization efficiency and research agility. The multimodal data-based specialized KD platform effectively breaks down data silos and creates high-quality research-ready data assets. It not only provides strong support for clinical diagnosis, treatment, and disease course management but also lays a solid foundation for conducting large-sample clinical studies and driving scientific innovation, significantly enhancing the hospitals core competitiveness in this field.

  Key words: Pediatric Kawasaki Disease; Specialized Disease Platform; Multimodal Data; Data Quality Control

  Submit time: 20 November 2025

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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  1	2025-09-10	10.12201/bmr.202511.00056V1	Download

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