COMPREHENSIVE MEDICAL DATA MANAGEMENT - HOLOGRAPHIC MEDASSISTANT

Proniewska K 1, Pręgowska A 2, Malinowski K 1, Dołęga-Dołęgowski D 1

1 Jagiellonian University Medical College, Poland
2 Polish Academy of Sciences, Poland

 

The project aims to develop a holographic medical assistant (Holographic MedAssistant) using an advanced holographic technology device - Microsoft's Azure Kinect DK camera and HoloLens 2 glasses. The project deals with digitalization and augmented reality use in rooms where doctors work, such as a doctor's office, an operating room, and a treatment room. The proposed solution will give new possibilities and enable additional support in the clinical diagnosis process, during medical procedures and the preview of the procedure from a different non-standard location without spatial restrictions related to the perspective of the Operator. The project will develop and implement methods for effective diagnostics and interpretation of biomedical signals and images (new effective classifiers) using Shannon's Information Theory and Artificial Intelligence (deep neural networks, spiking neural networks). It is planned to verify the proposed solutions using the methods of Biostatistics based on Mixed Models. The results obtained will allow doctor’s access to innovative tools supporting the clinical diagnosis process and performing medical procedures. Both, the system and the application will make a significant contribution to improving the quality of work, training and the quality of performed treatments. Moreover, result of the project has wide application field, among others: training of doctors, assisting during diagnostics through support in selecting a patient's disease with the use of artificial intelligence module, assisting physicians from other hospitals / medical facilities in performing more complex procedures, virtual medical consultations with specialists in other fields without having to leave the treatment room. The novelty of the project is to combine visualization of surgical room, the patient's medical data with an automatic interpretation regarding the patient's health status.

A new visualization tool for advanced personalized medical education has been proposed.

Acknowledgements:

Financed by NCBR. Grant No. LIDER/17/0064/L-11/19/NCBR/2020.