AI-assisted medicine: Minister Mohrs visits CAIMed research centre

How artificial intelligence can provide advanced support to doctors and nursing staff in hospitals.

Lower Saxony's Minister of Science Falko Mohrs and the Chairman of the Volkswagen Foundation Dr Georg Schütte visited the Lower Saxony Centre for Artificial Intelligence and Causal Methods in Medicine (CAIMed) at Hannover Medical School. They learned about current projects on AI-supported healthcare and personalised medicine.

Lower Saxony as a pioneer

'The visit to CAIMed confirms the exceptional quality of AI-based life science research in Lower Saxony, its direct benefits for clinical application and new diagnostic and therapeutic possibilities,' emphasised Minister Mohrs. Dr Schütte highlighted: 'The combination of state-of-the-art AI method development, excellent medical research and outstanding clinical practice creates a unique innovation ecosystem for the healthcare of tomorrow.'

Research with direct clinical benefits

'The methods developed at CAIMed show how artificial intelligence makes clinical decisions more precise and will shape the healthcare of the future,' said MHH President Professor Denise Hilfiker-Kleiner. CAIMed spokesperson Professor Wolfgang Nejdl added: 'Based on groundbreaking fundamental research and powerful foundation models, we develop AI methods that are technically advanced and transparent for doctors and nursing staff.'

Practical insights

Live demonstrations gave guests insights into where the medicine of the future is already becoming a reality today. In cytology, AI image analysis and deep learning enable better cervical cancer diagnostics. AI tools analyse thousands of cells in a very short time, flagging abnormalities and thus increasing the precision and speed of findings. In oncology, AI methods help identify extrachromosomal DNA, opening up new avenues for individualised therapies. Models also help to better predict long COVID and develop effective prevention strategies - a particular benefit for the long-term care of patients.

Application in everyday clinical practice

A great deal of effort is required to ensure that promising research finds its way into clinical application. There is great potential in paediatric intensive care, for example, where CAIMed researchers presented a prediction model for nosocomial sepsis that can provide early warning of impending blood poisoning with a high degree of accuracy, thereby contributing to patient care and reducing the burden on clinical staff. The telemedicine workstation can support children's hospitals throughout Lower Saxony and promote good healthcare across the region. In radiology, CAIMed researchers and clinicians demonstrated how AI-supported CT analyses enable faster and more accurate detection of pulmonary nodules, a major advance in speeding up diagnostics and reducing the burden on patients.

About CAIMed

The CAIMed consortium includes the AI research centre L3S at Leibniz University Hannover, Hannover Medical School, the Campus Institute for Data Science at the University of Göttingen, University Medical Centre Göttingen, the Helmholtz Centre for Infection Research and TU Braunschweig.

CAIMed is funded by the Lower Saxony Ministry of Science and Culture as part of the Volkswagen Foundation's zukunft.niedersachsen programme.

Text: Dr Johannes Winter