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Integration of Unstructured Data into a Clinical Data Warehouse for Kidney Transplant Screening – Challenges & Solutions

  • After kidney transplantation graft rejection must be prevented. Therefore, a multitude of parameters of the patient is observed pre- and postoperatively. To support this process, the Screen Reject research project is developing a data warehouse optimized for kidney rejection diagnostics. In the course of this project it was discovered that important information are only available in form of free texts instead of structured data and can therefore not be processed by standard ETL tools, which is necessary to establish a digital expert system for rejection diagnostics. Due to this reason, data integration has been improved by a combination of methods from natural language processing and methods from image processing. Based on state-of-the-art data warehousing technologies (Microsoft SSIS), a generic data integration tool has been developed. The tool was evaluated by extracting Banff-classification from 218 pathology reports and extracting HLA mismatches from about 1700 PDF files, both written in german language.

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Author:Maximilian Zubke, Matthias KatzensteinerORCiD, Oliver J. BottORCiDGND
DOI original:https://doi.org/10.3233/SHTI200165
Parent Title (English):Digital Personalized Health and Medicine : Proceedings of MIE 2020 (Studies in Health Technology and Informatics ; 270)
Document Type:Conference Proceeding
Year of Completion:2020
Publishing Institution:Hochschule Hannover
Release Date:2024/02/23
Tag:NLP; data warehouse; graft rejection; image processing; kidney transplant
GND Keyword:Automatische Sprachanalyse; Bildverarbeitung; Information Extraction; Data-Warehouse-Konzept; Transplantatabstoßung; Nierentransplantation
First Page:272
Last Page:276
Institutes:Fakultät III - Medien, Information und Design
DDC classes:610 Medizin, Gesundheit
004 Informatik
Licence (German):License LogoCreative Commons - CC BY-NC - Namensnennung - Nicht kommerziell 4.0 International