Artificial Intelligence-Based Decision Support in Laboratory Diagnostics

This research work introduces a solution approach for detecting infectious diseases in modern laboratory diagnostics. It combines an artificial intelligence (AI)-based data analysis by means of random forest methods with decision support based on intuitive information display and suitable planning functionality. The approach thereby bridges between AI-based automation and human decision making. It is realized as a prototypical diagnostic web service and demonstrated for the example of Covid-19 and Influenza A/B detection.