d.hip consists of four components:
With the implementation of d.hip projects, we set ourselves the goal of transforming different types of clinical data into smart prediction models together with our partners. In doing so, we are primarily concerned with disease patterns such as vascular diseases, stroke and diabetes. Thus, in the medium term, we are successively building a holistic model of a patient – the digital patient (Digita Health Twin).
In addition to these main topics, there is also the possibility of cooperation within the framework of so-called ad-hoc projects. Here, the aim is to rapidly implement ideas in the form of a prototype or proof of concept. You can find the rules of our projects in the category “Projects”.
In addition to the realisation of the d.hip projects, we intent to create an incentive to stimulate and support transdisciplinary cooperation in the area of innovations in digital health.
In our d.hip premises (former showroom of Siemens Healthineers) in Henkestr. 127, Erlangen, Germany, communities of interest meet regularly to discuss the latest developments in the field of Digital Health. Start-ups, companies, researchers, clinicians, ethicists and economists come together in our office to network or simply to inform themselves.
If you are also interested in hosting a conference, a hackathon, or co-creation sessions, please feel free to contact us by e-mail. We look forward to welcome you to our community. In addition to our event space, you will also find a makerspace, co-working workstations and well-equipped meeting rooms.
d.hip Data Center
The availability of clinical data is essential for health research in order to develop efficient methods to achieve the best predictions for diagnoses and therapies.
Our Data Center offers the unique opportunity to prepare clinical data in early 2020 for d.hip projects as an inclusive service for AI models. This includes both the query of the availability of the desired data at the University Hospital Erlangen, as well as the individually agreed refinement of the data (annotations, curation, anonymization, pseudonymization, …) in order to use them for your own algorithms.
Of course, the protection of the privacy of each patient and the compliance with the corresponding legal regulations within the framework of the General Data Protection Ordinance (GDPR) is maximally important to us. Only by respecting these requirements, it will be possible to achieve better results for the public health system.
Within the framework of the close cooperation with our partners, we are proud to significantly increase our personnel capacities at FAU. We are looking forward to four new colleagues who will come to Erlangen as W1 professors. The associated equipment is extremely attractive (financing, staff positions, industrial cooperation, …).