CARE REGIO

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CARE REGIO is a project funded by the Bavarian State Ministry that is developing innovative digital solutions for care together with partners from Swabia. The aim is to relieve the burden on carers and relatives through assistive systems and the digitalization of care processes. We create sustainable concepts that enable self-determined care and improved care - directly in Bavarian Swabia. Together we are shaping the digital care of tomorrow!

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DIFUTURE - Data Integration for Future 伟德国际_伟德国际1946$娱乐app游戏icine

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DIFUTURE is one of the four consortia of the 伟德国际_伟德国际1946$娱乐app游戏ical Informatics Initiative (MII), funded by the Federal Ministry of Education and Research (BMBF). The aim is to improve the networking and interoperability of health data through innovative IT solutions and thus promote their use for research and patient care. The focus is on providing use cases and software components as well as strengthening cooperation between university hospitals and other healthcare initiatives. In the long term, the aim is to create a digitally networked healthcare system that supports early disease diagnosis and individual therapy.

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GRAND-AID

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Finding the right skincare becomes easier: GRAND-AID uses AI to analyze skin conditions such as blemishes based on facial images. In collaboration with the Clinic for Dermatology and Allergology Augsburg and Grandel - The Beautyness Company, personalized skincare recommendations are created, which customers receive via a web application.

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Junior Research Group MoMoTuBo

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The junior research group Modular Knowledge- and Data-driven Molecular Tumor Board (MoMoTuBo) is developing a modular Molecular Tumor Board (MTB) to improve data integration, automation and documentation. The aim is to efficiently use clinical, genomic and other data, as well as external data, to enable reproducible therapy decisions.

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OCTOLAB

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The OCTOLAB project aims to revolutionize the early detection and minimally invasive treatment of basal cell carcinoma (BCC), the most common type of skin cancer. The use of artificial intelligence (AI) in the field of optical coherence tomography (OCT) enables precise diagnostics that accurately determine tumor thickness, extent and subtype. An Nd:YAG laser is also used to remove BCCs in a minimally invasive manner. The parameters of the laser are also adjusted based on the predictions of the AI. This innovative system could significantly improve the early detection and individualized, minimally invasive treatment of BCC.

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