In this interview, GeMTeX project managers Christina Lohr and Luise Modersohn explain how clinical texts can be used for AI, what challenges exist, and how clinics and research can benefit from this....
Clinical texts from routine care, such as doctors' letters, contain a treasure trove of data that is very valuable for research and clinical practice. The GeMTeX project aims to make this treasure accessible by preparing patient care texts for automatic language processing. The GeMTeX project...
International exchange is essential for the further development of the infrastructure of the Medical Informatics Initiative. The SMITH Consortium therefore met with the SMITH External Advisory Board to discuss the opportunities and challenges of the new funding phase of the MII. You can read about...
On 31 May and 1 June about 60 participants of the INTERPOLAR project met for the second INTERPOLAR Day in Leipzig. The focus of the event was on the coordination of drug safety and care standards in hospital pharmacy services as well as the integration...
On 30 and 31 May, around 40 members of the SMITH Consortium met for a closed meeting at the Albertina Library of the Leipzig University. The second meeting of the year focused on the further development of the consortium's cooperation and technical harmonisation in the...
Routine care generates large volumes of medical text that contain valuable information about patients. However, the wording, content and structure of medical documentation can vary greatly between different institutions, making it unusable for digital programmes or analysis across different locations. In the SMITH consortium, the...
Through the work of the Medical Informatics Initiative (MII) and the associated establishment of Data Integration Centres, a unique and rich pool of clinical care data from various areas of healthcare is being made available for research. Unique because the form and content of this...
Making routine clinical data available for medical research is an essential building block for progress in medicine. Individualised therapies and even more precise diagnoses will thus be possible in the future. In addition, health data provide a basis for the development of digital technologies to...
The SMITH Junior Research Group "Terminology and Ontology-based Phenotyping" (TOP) aims to implement an easily accessible ontology-based software platform for modelling and executing phenotype algorithms. The so-called TOP framework is implemented as a modular web application that combines various software tools and services for algorithmic...
AI and machine learning can optimize intensive care medicine, e.g., by predicting disease progression. In this interview, Konstantin Sharafutdinov explains how virtual patients can help with this....