Refine
Document Type
- Conference Proceeding (2) (remove)
Language
- English (2)
Has Fulltext
- yes (2)
Is part of the Bibliography
- no (2)
Keywords
- Automatische Sprachanalyse (1)
- Bildverarbeitung (1)
- Citizens (1)
- Data-Warehouse-Konzept (1)
- Didactic (1)
- Digitalisierung (1)
- Digitalization (1)
- Digitization (1)
- E-Learning (1)
- Gesundheitsfürsorge (1)
- Health IT (1)
- Information Extraction (1)
- NLP (1)
- Nierentransplantation (1)
- Patient empowerment (1)
- Transplantatabstoßung (1)
- data warehouse (1)
- eLearning (1)
- graft rejection (1)
- image processing (1)
- kidney transplant (1)
Institute
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.
Building a well-founded understanding of the concepts, tasks and limitations of IT in all areas of society is an essential prerequisite for future developments in business and research. This applies in particular to the healthcare sector and medical research, which are affected by the noticeable advances in digitization. In the transfer project “Zukunftslabor Gesundheit” (ZLG), a teaching framework was developed to support the development of further education online courses in order to teach heterogeneous groups of learners independent of location and prior knowledge. The study at hand describes the development and components of the framework.