The invention relates to the technical field of oral
abutment three-
dimensional modeling, and discloses a method for optimizing oral
abutment three-
dimensional modeling by utilizing a
machine learning
algorithm, which comprises the following steps of: 1, acquiring detection data of an
oral cavity of a patient and a three-dimensional size of an
implant, and classifying to form a
data set; 2, analyzing the
crowding degree and occlusal force distribution state of the teeth of the patient, and generating a
crowding ratio and a distribution index; 3, analyzing the inclination of
anterior teeth of the patient, evaluating the
occlusion relationship of the teeth of the patient, and setting a conversion coefficient for converting the three-dimensional size of the
implant into the three-dimensional size of the oral
abutment; 4, the three-dimensional size of the
oral cavity abutment is simulated, an abutment
data set is generated, and the personalized
adaptation capacity is high; and step 5, constructing an
oral cavity three-dimensional model, an
implant three-dimensional model and an oral cavity abutment three-dimensional model of the patient, setting a fixed threshold value, evaluating the fitness of the oral cavity abutment three-dimensional model, and outputting optimization suggestions, and the comfort level of optimization modeling is high.