The application relates to a jaw and
facial bone fracture
internal fixation plate selection decision method and
system, which belongs to the technical field of medical
artificial intelligence and relies on a pre-trained degradable
internal fixation material prediction model and a
titanium internal fixation material prediction model. The two kinds of
implant materials can be simultaneously quantitatively evaluated based on the same preoperative characteristic data of a patient, the risk levels of the two kinds of materials are divided by corresponding threshold values, and then individualized
material selection suggestions are output by combining double
risk level linkage determination rules. Unlike the traditional
selection method which only relies on the subjective judgment of the clinical experience of doctors, the method realizes the quantitative correlation between the baseline characteristics of the patient and the prognosis risk of the material, avoids the defect that a
single group comparison conclusion cannot adapt to individualized diagnosis and treatment, quantitatively evaluates the objective and repeatable
risk assessment results, effectively improves the scientificity and precision of the selection of the internal fixation material for the jaw and
facial bone fracture, and reduces the probability of selecting an unsuitable
implant material for a patient with a high complication risk.