## 3 Defining the Use Cases: The Gaia-X-Med Project
### The Six Use Cases
Furthermore, to improve the accuracy of this prediction, long-term outcomes and risk factors are identified by also incorporating routine patient data like age, height, weight, chronic illnesses other than the heart diseases in question of both affected and unaffected patients into the model. This prediction is presented as an application for research use by medical professionals, relying on the personal and biometric data of individual patients, requiring their consent, as well as anonymized routine data, which could be obtained via ethical approval by an associated hospital's data integration center (DIC), the data of which are collected with broad consent for research use. Use Case 3 (green)--AI-based home monitoring of eye diseases. Regularly obtaining OCT images of the eye can improve the diagnosis and rehabilitation recommendations made by medicinal professionals. The OCT devices provided to patients at home help in obtaining these images and strongly improve patient acceptance, while the automatic segmentation provided by a commercial application for medical professionals further assists in making treatment decisions. The employed data are personal and biometric, and their usage requires individual patient consent when using the OCT device and sending the data to be segmented. At the same time, the segmentation process itself may be improved further using these data or is itself based upon other personal patient data, which in turn will need and would have needed individual patient consent for this type of usage. Use Case 4 (yellow)--AI-based causal inference. Classifying genetic predispositions remains an interesting field of research. Connecting the researchers working on classification algorithms and AI models with other researchers able to provide the genetic datasets to train them is facilitated by an open collaborative platform. This application for research use requires data protection measures for each collaboration taking place. If one researcher intends to provide data for another, the initial data protection concept of when the data were collected has to be checked for whether it permits this forwarding, as far as it is possible with broad consent. Additionally, if classification was to be performed on actual patients, additional regulations would apply. Use Case 5 (black and white)--HACCP in a Smart Hospital. The state veterinary office has a duty to monitor hygiene processes in hospitals. In order to facilitate this, hygiene sensors--particularly temperature sensors in freezers--are deployed in the hospital and a monitoring application is developed. This commercial application for a state institution has few regulations regarding the privacy of the collected data, since the exchanged data are not personal. Use Case 6 (grey)--Decision Support System. The domain knowledge of medical experts can be formalized as models. Using large language models (LLMs) to generate textual explanations from these models can be useful for providing diagnosis assistance to medical professionals. A research use application for medical professionals is developed that does not rely on individual patient data but rather on models created by experts, often based on medical literature or guidelines, and is thus not subject to the associated data protection regulations. In each use case, a Gaia-X-based demonstrator shows the feasibility of the concept, keeping in mind the associated data protection regulations, which typically represent a major challenge during the development of eHealth applications, so as to lay a foundation for later commercialization, if intended. In the following, we take a closer look at the use cases' requirements with respect to Gaia-X's services.