The invention discloses a multi-
modal data fusion-based
rheumatoid arthritis early-stage AI intelligent diagnosis
system, belongs to the technical field of medical
artificial intelligence, and aims to solve the problems that in the prior art, RA early-stage diagnosis lags behind, the rate of
missed diagnosis of serum negative patients is high, and
risk assessment lacks quantitative standards. Comprising a multi-
source data acquisition module, a data preprocessing module, a cross-
modal fusion module, a dynamic
time sequence model and a
risk assessment module which are connected in sequence, according to the
system provided by the invention, a dynamic
tracking model of serological change-synovial
inflammation-
bone structure change is innovatively constructed, and an RA diagnosis window is advanced compared with that of a traditional method (depending on clinical symptoms) by capturing
time sequence correlation of the serological change, the synovial
inflammation and the
bone structure change; aiming at the diagnosis difficulty of serum-negative RA, the
system realizes great improvement of diagnosis performance through deep fusion of multi-
modal features, serological core indexes, ultrasonic synovial dynamic features and X-
ray bone microscopic features.