The e/MTIC AI-Lab is aimed at improving personalized treatment by having AI work in close collaboration with the clinical staff and MedTech industries since AI is better able to make reliable decisions in a wide range of healthcare situations.

The goal of the e/MTIC AI-Lab is to work with a unique mixture of industry, clinical partners and TU/e researchers to maximize the value of AI for the clinical practice.

Given that the main purpose of e/MTIC is to provide a “Fast track to clinical innovation”, Artificial Intelligence is an extremely important instrument to support this goal. Both in clinical decision support in general, and in-patient monitoring and image analysis in particular, novel AI techniques provide powerful approaches to identify patient deterioration at an earlier stage, diagnose conditions more accurately, better guide treatment, and improve secondary prevention.

ICAI is a Dutch network aimed at technology and talent development between knowledge institutes, industry, and government in the area of artificial intelligence. 

2022 ICAI Deep-Dive Data Series I: Medical data usage

What if we would remove many of the roadblocks, researchers and clinicians face while exchanging Medical Data from multiple sources? To drive value-based health care, we need to analyze massive amounts of data. Finding, accessing, and processing medical data while respecting privacy and security regulations is a complex task.

During the hybrid event ICAI e/MTIC of 12 May 2022, we addressed how data sharing and AI play an essential role within e/MTIC and share with you two research cases in which data and AI play a vital role.

e/MTIC AI Health projects

Many of the e/MTIC researchers are currently working on and implementing analysis techniques and (prediction) algorithms for improved (patient) monitoring and diagnosis and to help optimize individual treatment strategies in collaboration with many medical specialists.

From Bench to Bedside ->



Research Topics

Many e/MTIC researchers are currently working on analysis techniques and algorithms for improved (patient) monitoring and diagnosis to help optimize individual treatment. Due to the many complexity and heterogeneities in medical data, these approaches will be further developed, implemented and automated through projects in e/MTIC. The research focus is on robustness and improved stability of algorithms and methods.

In the e/MTIC AI-Lab, AI will be mainly used for the following application areas:

- Imaging :
strongly enhanced Ultrasound, MRI and CT imaging by embedding task-adaptive AI across the imaging chain

- Patient monitoring :
strongly enhanced monitoring of vital signs both in clinical and in extramural settings

- Clinical decision support systems :
 use AI to combine various data streams (e.g. EMR, images, spot checks) to produce explainable and patient-specific advice, early warning and alarms.

e/MTIC Health Data Portal

The partners of e/MTIC joined hands to develop the Health Data Portal (HDP) to facilitate and enable joint research projects. The e/MTIC HDP is a scalable collaboration platform that builds on existing initiatives to provide an infrastructure where medical data from multiple institutions can be shared safely and researchers can collaborate on this data.

The construction of the e/MTIC HDP platform allows, for the first time, medical data from different types of healthcare institutions to be shared securely and anonymously, such as between hospitals, universities and industry. The HDP has an important role in the national network of the Health-RI project, financed by the National Growth Fund.

Our team