A machine learning-based infant developmental condition predicting method and apparatus, a storage medium, and an electronic device, relating to the technical field of computer programs. The method comprises: obtaining single-time limb movement data of a sample to be detected and corresponding month age data (101); performing data processing on the single-time limb movement data of said sample to obtain a characteristic value, corresponding to the month age data, for single-time limb movement for said sample (102); substituting characteristic values of the predetermined number of times of the single-time limb movement corresponding to said sample and the corresponding month age data into a mathematical model of a stacked extreme learning machine for performing logic operation (103); and obtaining a prediction result of an infant developmental condition by using an output result of the logic operation of the stacked extreme learning machine as a basis of normal development or retarded development of said sample (104). The apparatus, the storage medium, and the electronic device can be used for achieving the infant developmental condition predicting method. By means of the method, the developmental condition prediction can be performed on infants, the possibility of infant development retardation is further obtained, and accordingly, a reliable basis can be provided for early intervention of the infant development retardation.
MACHINE LEARNING-BASED INFANT DEVELOPMENTAL CONDITION PREDICTING METHOD AND APPARATUS, STORAGE MEDIUM, AND ELECTRONIC DEVICE