With around 500,000 cases annually in Germany alone, hospital infections pose a considerable medical, organisational and economic challenge. Approximately 20,000 of these cases are fatal. Manual analysis of patient and laboratory data is time-consuming, prone to errors and sometimes too slow to interrupt chains of infection in time.
PathoBot addresses this problem with a software solution that combines rule-based and AI-supported processes. Gaussian processes and self-organising maps enable automated evaluation of existing laboratory data and potential patient contacts with regard to current transmission events. This allows chains of infection to be identified more quickly, increases the number of identified transmissions and significantly reduces the workload for hospital staff.
Through automated evaluation of medical data, PathoBot reduces the workload for medical and diagnostic professionals and supports the early detection of suspected cases. At the same time, patients benefit from faster detection of potential chains of infection and thus from improved protection against hospital-acquired infections.