The invention discloses an early noninvasive
endometrial cancer assessment method based on
machine learning, and the method comprises the following steps: S1, obtaining the index data of a potential endometrial
lesion patient in advance, and carrying out the
data integration based on the index data according to a preset standard to obtain a
feature set; s2, performing standardized preprocessing on the
feature set in the step S1 to obtain a
training set and a
test set of standardized endometrial
lesion data; s3, constructing a
disease prediction model based on a preset multi-
modal machine learning model and used for predicting an
endometrial cancer result on the basis of the
training set and the
test set containing the endometrial
lesion data obtained in the step S2; and S4, inputting endometrial lesion index data of a patient to be evaluated into the
disease prediction model to implement early noninvasive
endometrial cancer prediction evaluation so as to obtain an endometrial
cancer prediction result of the patient. The method has the advantages that non-invasive screening can be met at the same time, the prediction accuracy is high, and the economic burden is small.