F.A.I.T.H. – First Aachen EIT Health Hackathon

Join our first Hackathon in Aachen & learn how Big Data drives Innovation in Healthcare

Despite being the most technologically advanced field in medicine, intensive care medicine lacks essential automation in pre-processing the high volume-velocity data generated. However, effectively analyzing and utilizing this complex data can support the detection of life-threatening patient conditions and enable automated monitoring of a large number of patients. Consequently, this would allow relieving the burden from physicians and enable them to spend more time with patients. Current research trends use this data volume and elaborate machine learning algorithms to extract and target the patterns present there to predict critical phases,understand complex diseases and provide smart assistance functions.

Therefore, we are pleased to organize the First Aachen EIT Health Hackathon (F.A.I.T.H) with our partners EIT Health, MIT Critical Data, Clinomic GmbH, the Universitätsklinikum Aachen - Klinik für Operative Intensivmedizin und Intermediate Care and TechLabs Aachen e.V. to give Health Care Professionals/Data Scientists/Students from the EIT Health Community and local universities the first insight into this exciting and vital field.



The hackathon will take place on the weekend July 25th/26th and goes from 9am to ~6pm on both days. The teams will work on their projects during these two days. Moreover, we’ll offer interesting presentations during these two days, but except these events the hackathon will primarily be focused on working in the teams and, thus, does not offer e.g. workshops and panels. The detailed agenda will be published in early July. Besides, we plan to host all keynotes publicly via Zoom.

Note about required experience level

The event is open to everyone (since it will be an educational event), but we need you (if you are not a healthcare professional) to have intermediate-level Python experience (as taught in the TechLabs #DigitalShaper program) which means you must be able to work with pandas, matplotlib and some other data science/mathematics libraries (e.g. NumPy). Of course, you don’t have to be an expert in these libraries, but ideally you should have some basic experience.

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