This application discloses a medical
data processing method, apparatus, equipment, and medium for
nonunion healing analysis, relating to the field of medical and
health information technology. The method includes: quantitatively
processing CT images and biochemical indicators of the target area to obtain fracture gap parameters and microenvironment
biological activity scores; inputting the gap parameters, activity scores, and
implant information into a multidimensional
etiology association model to calculate
etiology weight vectors; extracting visual morphological feature vectors from CT images at multiple scales using a three-dimensional image network; constructing and simulating a three-dimensional finite
element model based on CT images and
implant information to obtain biomechanical feature vectors; weighting and fusing visual and mechanical features according to the
etiology weight vectors to obtain cross-
modal collaborative features; and
processing the data through a multi-task prediction network to obtain scoring auxiliary data and dynamic healing prediction curves. This application can obtain accurate quantitative analysis reference data based on multi-source heterogeneous medical data to assist in the classification assessment of
nonunion and the prediction of dynamic healing trends.