DMEA 2025

Trade exhibition and congress for digital healthcare / April 08, 2025 - April 10, 2025

Connecting Digital Health

DMEA is Europe's leading event for digital health, bringing together experts from healthcare, IT, and research to explore the future of healthcare technology. The upcoming DMEA 2025 will take place from April 8 to 10, 2025, at Messe Berlin in Germany. The event features keynote speeches, panel discussions, and exhibitions showcasing the latest innovations in healthcare IT, artificial intelligence, telemedicine, and digital patient care. It serves as a central platform for networking, knowledge exchange, and collaboration, driving the digital transformation of healthcare.

The experts of the Fraunhofer Institute for Digital Medicine MEVIS are looking forward to welcoming you at the joint booth of the Fraunhofer-Gesellschaft (Hall 2.2 | Booth D-109).

At this year's DMEA Fraunhofer MEVIS presents AI-powered solutions for informed decisions and better patient care:

Harmonized tabular health data for AI development
Image Foundation Models for Digital Biomarkers
Sensor-Based Monitoring for Patients with Heart Failure
Assistant LUKAS for advanced Patient Care and Nursing Efficiency

Event details

Location

Messe Berlin
Berlin ExpoCenter City
Booth of Fraunhofer-Gesellschaft: Hall 2.2 | Booth D-109
Messedamm 22
Berlin

Date

April 08, 2025 - April 10, 2025

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Harmonized tabular health data for AI

Fraunhofer MEVIS develops software to preprocess data for AI training. Our demonstrator INDAST enables efficient data harmonization and mapping from various sources, while MARATUS offers a visual web interface for setting up and applying data preprocessing chains without the need for coding.

Medical data evaluation from clinical studies to AI model generation requires adequate preprocessing. Necessary information from the collected tabular raw data must be extracted, harmonized and transformed into suitable formats. Further preprocessing steps include appropriate value encoding, missing data handling or feature engineering.

At DMEA, we exhibit our data preprocessing tools, provide insights into their usage and customization and advise on application possibilities in specific areas of use.

Image Foundation Models for Digital Biomarkers

The authors thank the National Cancer Institute for access to NCI's data collected by the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial.

Our experts have developed and implemented a supervised training approach that achieves results while using only 1% of the computational resources and energy. This approach makes training foundation models significantly more cost- and energy-efficient.

Foundation models are AI-based models that are pre-trained with a variety of training data to learn general patterns or features. In histopathology, foundation models are the basis for new image-based biomarkers, e.g. for predicting patient risk or therapy response, which will help to reduce costs in personalized medicine.

At DMEA, we show how foundation models can be used to train AI on clinical outcome data and how these models can generate new insights into image-based biomarkers.

Sensor-Based Monitoring for Patients with Heart Failure

Fraunhofer MEVIS presents a non-invasive wearable sensor system, and an interactive clinical dashboard designed to monitor the disease progression of heart failure patients.

The system integrates various sensors, including a smart scale, chest strap, wrist band and a digital stethoscope to track key health metrics.

A mobile app guides users through their daily measurements, ensuring adherence to clinical study protocols. After the health data is collected and analyzed, it is visualized through the interactive clinical dashboard.

This allows healthcare professionals to monitor trends and effectively communicate progress with patients. All participants accepted the system and found it easy to use.

At DMEA, we will showcase our sensors, mobile app, and clinical dashboard.

Assistant LUKAS for advanced Patient Care and Nursing Efficiency

LUKAS is an assistance system for nursing wards in hospitals that is used by both patients and nursing staff via voice and touch control. It is designed to improve the quality of stay for patients, to provide comprehensive information and to simplify documentation requirements and the coordination of care processes.

A unique feature of LUKAS is its ability to obtain information from a variety of sources and evaluate it independently. LUKAS draws on data from the clinical information system, the nursing documentation system and various sensors such as sleeping mats and wearable devices.

During the working day, LUKAS carries out documentation tasks as automatically as possible and can go through open points with the nursing staff at the end of the shift. This significantly reduces the manual documentation effort and helps to avoid gaps in documentation.

In situations when quick communication is required, LUKAS can proactively contact both patients and nursing staff making him a reliable partner in everyday nursing.

Visit us at DMEA 2025 (Hall 2.2 | Stand D-109) and discover our innovative solutions for digital medicine!