An AI-generated weight management method
An artificial intelligence and management method technology, applied in the field of artificial intelligence-generated weight management, can solve problems such as weak flexibility and diversity, inability to form metabolic balance, and uncontrollable appetite, so as to reduce the level of fasting insulin secretion and increase the daily average. Food intake and the effect of increasing resting metabolic rate
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specific Embodiment 1
[0046] A kind of artificial intelligence generates weight management method, described method comprises the following steps:
[0047] Step 1: Obtain basic personal information
[0048] Step 2: Establish a database based on the data of the individual's age, weight, waist circumference, blood sugar, and blood pressure;
[0049] Step 3: According to the individual's data, intelligently identify whether the individual belongs to a certain category, and if it belongs to a certain category, classify the individual into the existing category of the crowd database. If no existing classification is found, the individual will be sent to a professional nutritionist for manual classification, and machine learning technology will be used to train the system to obtain a new plan and finally verify the effectiveness of the plan. When 300 individuals exceed 95% effectiveness, the scheme library of the classified population library will be formed.
[0050] Step 4: Synchronize the time stamp ...
specific Embodiment 2
[0059] A kind of artificial intelligence generates weight management method, described method comprises the following steps:
[0060] Step 1: Obtain basic personal information
[0061] Step 2: Establish a database based on the data of the individual's age, weight, waist circumference, blood sugar, and blood pressure;
[0062] Step 3: According to the individual's data, intelligently identify whether the individual belongs to a certain category, and if it belongs to a certain category, classify the individual into the existing category of the crowd database. If no existing classification is found, the individual will be sent to a professional nutritionist for manual classification, and machine learning technology will be used to train the system to obtain a new plan and finally verify the effectiveness of the plan. When 300 individuals exceed 95% effectiveness, the scheme library of the classified population library will be formed.
[0063] Step 4: Synchronize the time stamp ...
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