Hospital crowdedness evaluation and in-hospital resource allocation based on image recognition technology.

ABSTRACT: How to allocate the existing medical resources reasonably, alleviate hospital congestion and improve the patient experience are problems faced by all hospitals. At present, the combination of artificial intelligence and the medical field is mainly in the field of disease diagnosis, but lacks successful application in medical management. We distinguish each area of the emergency department by the division of medical links. In the spatial dimension, in this study, the waitlist number in real-time is got by processing videos using image recognition via a convolutional neural network. The congestion rate based on psychology and architecture is defined for measuring crowdedness. In the time dimension, diagnosis time and time-consuming after diagnosis are calculated from visit records. Factors r

SUBMITTER: Deng L 

PROVIDER: S-EPMC9822910 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature