PASBADIA (Patient-side Smartphone-based Diagnostics with local and central AI Platform for Primary Care in rural Areas)
||Prof. Dr.-Ing Horst Hellbrück|
In the joint project PASBADIA at the Lübeck campus Technische Hochschule Lübeck and the University of Lübeck develop solutions for smartphone supported patient-side diagnostics with local and decentralized AI. In cooperation of engineers, natural scientists and practicing medical specialists, new diagnostic solutions are desigend and developed.
In medicine, a fast, patient-side diagnosis is helpful. For example, in monitoring the curative course of patients in rural areas, with restricted mobility, in poorly accessible or underserved areas, the use of widely available diagnostic devices is a promising approach. Current smartphones are suitable for this task due to their widespread use and the already built-in sensor technology and computing capacity, but are applied only occasionally.
The high-quality cameras together with light sources (LED flash) built into smartphones enable implementation of optical diagnostic solutions from the field of classic devices, if the corresponding attachments and applications are adapted to the smartphone and measurement data are evaluated on site.
The aim of the subproject of CoSA is the distributed collection, storage and processing of data with limited resources in the challenge between the methods of the AI, the available database and partially low or missing Internet connection in rural areas.
The Laboratory for Ophthalmology (LfO) develops robust and safely applicable optical attachments for smartphones as a combination of spectral, fluorescence or polarization-based methods to generate and analyze raw diagnostic data at the fundus of the eye.
The efficient data-based evaluation of these raw data with modern methods of statistical learning theory, in the field of probabilistic graphical models and efficient Gaussian process analysis with integration of prior knowledge as well as stochastic uncertainty information is researched by the Institute of Electrical Engineering in Medicine (IME).
At the Institute of Family Medicine (IfA), the needs in the field of ophthalmology are assessed by targeted analysis of processes in primary care and exploration of the determinants for successful implementation of the technical applications to be developed in everyday care.
The task of this interdisciplinary cooperation is summarized in the following central question:
How efficiently can an AI-based diagnostic tool based on a smartphone support a general practitioner in carrying out the ophthalmological diagnostics required in (basic) care close to the patient's home (and thus relieve the ophthalmologist of the burden of specialistically active area physicians, for example)?