Diabetes digital management method
A management method and diabetes technology, applied in the field of medical data management, can solve problems such as limitations, lack of exercise and dietary intervention, lack of active patient control, etc., to achieve the effect of efficient physical recovery
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Embodiment 1
[0070] An embodiment of the present invention provides a digital management method for diabetes, including:
[0071] Obtain the body data of diabetic patients, perform preprocessing on the body data, and send the preprocessed data to a preset big data processing platform;
[0072] Analyze the preprocessed data based on the big data processing platform, and send the analysis results to the data transmission ports corresponding to the sportsman and the nutritionist, and determine the sports nutrition plan;
[0073] According to the sports nutrition program, the patient's exercise and diet data are tracked and recorded in real time through the terminal application program, and the sports nutrition program is dynamically adjusted according to the recorded data;
[0074] The working principle of the above technical solution is: in the prior art of the present invention, the clinical data of the diabetic patients are obtained, the clinical data is preprocessed, the preprocessed clin...
Embodiment 2
[0079] In one embodiment of the present invention: said acquiring the body data of a diabetic patient, performing preprocessing on said body data, and sending the preprocessed data to a preset big data processing platform, includes:
[0080] Perform data filtering according to the physical data of the diabetic patient, obtain data to be processed, and perform data cleaning on the data to be processed to obtain primary processing data; wherein, the physical data includes: blood sugar data, liver data, muscle data , fat data, pancreas data, intestinal data, urine data, etc.; the data to be processed includes: missing data, noise data, repeated data;
[0081] classifying the primary processing data according to a preset data format, obtaining heterogeneous data, and performing data integration on the heterogeneous data to obtain secondary processing data;
[0082] Converting the secondary processing data to standard deviation data, obtaining the tertiary processing data, and sync...
Embodiment 3
[0088] In one embodiment of the present invention: said acquiring the body data of a diabetic patient, performing preprocessing on said body data, and sending the preprocessed data to a preset big data processing platform, further includes:
[0089] Comparing the preprocessed data with a preset threshold range to determine whether the body data is within the preset threshold range;
[0090] When the physical data is not within the preset threshold range, it is determined that the physical data is abnormal physical data;
[0091] When the physical data is within a preset threshold range, it is determined that the physical data is normal physical data;
[0092] Based on the preset diabetes detection platform, detect the abnormal body data of the patient, obtain the detection results, and store the detection results in the cloud server,
[0093] According to the detection results of the diabetic patients, the detection results are graded to obtain the diabetes grade classificati...
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