ODIN Project‘s #ReferenceUseCases (1/3)
Based on the needs of the pilots participating in the ODIN Project, seven use cases were defined. Considering these and the objectives and categories covered by each of them, it has been chosen to introduce three Reference Use Cases (RUCs) overarching all the case studies to be included in ODIN.
In this blog article we are going to concentrate on RUC A. Articles on RUC B and RUC C will follow.
RUC A – #health #services #management
This reference use case encompasses the use cases focused on the clinical (and diagnostic) oriented activities that the ODIN project addresses.
The use case «AI-based support system for #diagnosis» focuses on the use of #AI technologies to optimise the personalised search for the diagnosis considered most effective in each case. It is serving as a support to #healthcare #professionals in decision-making, considering probabilities as well as the capacity of available diagnostic modalities.
The use case «Clinical Tasks and #patientexperience» is the use case with most of the #pilots involved within the RUC A. It aims to reduce the effort that clinical personnel must exert in therapeutic and diagnostic activities based on ODIN #technology. This should not only improve the #quality
and #workflow of clinicians, but also optimise the comfort perceived by patients during their journey through the healthcare system and to improve their health #conditions.
Likewise, the use case «#Automation of clinical workflows» aims to respond/act against the emerging difficulty within workflows, which often follow processes that are not efficient enough. Therefore, this project, taking advantage of workflows and the collection of data and sources.It aims to offer a solution by automating #clinicalresearch execution processes in order to reduce possible errors.
Finally, the use case «Inpatient remote rehabilitation» focuses on remote patient monitoring covering both patient follow-up and simple and secure communication between patients and the relevant #hospital sector. To this end, the ODIN project will deploy an AI system to automatically support patients and help healthcare staff to provide optimized lifestyle monitoring.
RUC A aims at maximizing data-driven decisions and supporting execution of clinical tasks through the adoption of ODIN robotic and IoT platforms. In this reference use case, the ODIN AI methods are exploited for all tasks, from Admission & Screening to Follow up, together with IoT and Robotic platform (e.g. to reduce workload of workers during the treatment of the patient). Standard interfaces, such as system communication protocols, are also relevant to promote interoperability among departments in charge of the different phases and with the #outclinics and #homecare settings.