PhD Candidate · IKIM Essen
Bahadır Eryılmaz
Doctoral researcher at the Institute for AI in Medicine, exploring how language models and computer vision can make healthcare more accessible, interoperable, and personalized.
Research Areas
What I Work On
LLMs in Healthcare
Exploring how large language models can transform clinical workflows, from automating FHIR resource generation to supporting clinical decision-making.
Computer Vision
Investigating reproducibility in medical image analysis and developing robust visual understanding systems for healthcare applications.
FHIR & Health Data
Building interoperable healthcare data systems using HL7 FHIR standards, enabling seamless data exchange across clinical platforms.
Personalized Medicine
Leveraging AI to tailor medical treatments to individual patients, combining genomics, clinical data, and machine learning.
Selected Work
Featured Publications
Enhancing Healthcare Interoperability Using Large Language Models: A Generative Proof-of-Concept Framework to Extract Medical Information from Unstructured Clinical Text
JMIR (Preprint)
Automated Tumor International Classification of Diseases Coding of Real-World Pathology Reports Using Self-Hosted Large Language Models
JCO Clinical Cancer Informatics
Overview of ImageCLEFmedical 2025 – Medical Concept Detection and Interpretable Caption Generation
CLEF 2025
Using a Diverse Test Suite to Assess Large Language Models on Fast Health Care Interoperability Resources Knowledge: Comparative Analysis
Journal of Medical Internet Research
Interested in Collaborating?
I'm always open to research collaborations in AI and healthcare. Let's connect and explore how we can work together.
Get in Touch