Hajira Jabeen
PhD
Large Language Models
Large Language Models are transforming the way we process and understand biomedical data. In our research, we study how these models can be adapted to the specific challenges of medicine and life sciences—for example, by extracting knowledge from clinical records, supporting structured data integration, or assisting healthcare professionals with decision-making. At the same time, we critically assess the limitations of LLMs to ensure their applications remain robust, transparent, and safe for real-world use.
Publications
Real-Time Visualization and Analysis Architecture for Data Integration Processes at Cologne University Hospital's Medical Data Integration Center
2025
This case study discusses the effectiveness of implementing a real-time automated monitoring architecture using the ELK Stack (Elasticsearch, Logstash and Kibana) to ensure data ingestion quality within the Medical Data Integration Center (MeDIC) at the University Hospital Cologne. By streamlining the ETL (Extract, Transform, and Load) log analysis process, this system minimizes the need for manual effort and brings increased efficiency and precision in analyzing data quality issues in real-time, detecting errors and potential problems, including the ability to uncover new errors. Over a six-month period, the implemented dashboard was able to process the ingestion logs of millions of files to provide valuable insights for the stakeholders in the decision-making process.