LLM4Anamnese: Automation and standardization of medical history texts

The LLM4Anamnese project aims to use Large Language Models (LLMs) to automatically classify medical histories, which are often recorded in free text form, and link them to standardized medical terminology. This automation not only facilitates the further processing of the texts in digital systems, but also improves data quality without losing the individual aspects of the patient histories.

A particular focus of the project is on researching how resource-efficient and robust LLMs can work in practice. The application in everyday clinical practice will be tested under real conditions to ensure that the technology meets the high requirements of the healthcare system. The adaptation of LLMs to medical data is a key step in optimizing the classification of texts and making the results usable for other medical applications.

In the long term, the project should help to relieve the burden on medical staff and improve the quality of patient care.