3 results about "Primary osteoporosis" patented technology

The present application relates to the technical field of multi-cause intelligent analysis in medical diagnosis, and particularly relates to an osteoporosis detection method and system based on data analysis and artificial intelligence. The method comprises the following steps: S1: obtaining primary osteoporosis data and secondary osteoporosis data and determining synergistic data, and determining antagonistic masking data according to the synergistic data; S2: obtaining a first layer dominant right conversion sequence according to the synergistic data and the antagonistic masking data; S3: obtaining a synergistic data internal dominant relationship sequence and an antagonistic masking data internal dominant relationship sequence respectively according to the synergistic data and the antagonistic masking data, and generating a complete dominant relationship graph in combination with the first layer dominant right conversion sequence. The present application separates and analyzes the synergistic and antagonistic modes of primary and secondary osteoporosis, constructs a dynamic dominant right sequence, quantifies the evolution of mixed cause weights, and provides data support for individualized precise diagnosis and treatment.

The present application relates to a kind of metabolic markers for diagnosing diabetes secondary osteoporosis and its application, belong to biological medicine technical field.The present application first selects the significant difference metabolite between the group of diabetes mellitus patients with osteoporosis (DOP) and the group without osteoporosis (DM);Second, the significant difference metabolite between the group of primary osteoporosis patients and the group of healthy controls is screened out, and the intersection of the two groups of difference metabolites is excluded, and the obtained metabolite excludes the influence of primary osteoporosis.Subsequently, the metabolic markers of the present application-cytidine nucleotide, ketoglutaric acid, triethylamine are further screened, and when the three kinds of metabolic markers are used alone, the AUC is greater than 0.8, and when the three kinds of metabolic markers are used in combination, the AUC is 0.99, effectively making up the limitation of traditional bone density detection in the population of diabetes mellitus patients to identify osteoporosis.

The embodiment of the invention discloses an osteoporosis secondary screening method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring medical data to be screened; preprocessing the medical data to be screened; performing feature extraction and combination on the processing result to obtain data features; inputting the data features into an osteoporosis secondary screening model for prediction to obtain a prediction result; outputting a prediction result; the osteoporosis secondary screening model comprises a primary osteoporosis screening model which is obtained by training a gradient lifting machine learning model through a sample set formed by processing medical data with labels indicating whether sample bone mass is abnormal or not; the second-level osteoporosis screening model is obtained by training a neural network through a sample set formed by performing feature fusion on an output result of the first-level osteoporosis screening model and a medical examination data subset. By implementing the method provided by the embodiment of the invention, the accuracy of screening high-risk groups with osteoporosis in middle-aged and elderly women can be improved.