Doctor-patient management system and method based on Internet artificial intelligence
An artificial intelligence and management system technology, applied in the field of doctor-patient management system, which can solve the lack of mechanisms and methods for patient filing and updating outside the hospital, the inability to achieve a long-term stable relationship between doctors and patients, and the inability to achieve a long-term stable relationship between doctors and patients. To improve the quality of medical services, reduce the risk of recurrence and deterioration, and avoid medical errors
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example 1
[0113] Example 1: Structured patient A's medical information forms n pieces of information containing:
[0114] 1. Gender (male)
[0115] 2. Age (67 years old)
[0116] 3. Diagnosis (coronary heart disease)
[0117] 4. Treatment method (percutaneous coronary stent implantation)
[0118] 5. Processing time (October 15, 2019)
[0119] The first collection with a large amount of guideline data is obtained by screening the guideline database with article 1 (gender (male));
[0120] Then use item 2 (age (67 years old)) to filter the first set to obtain the second set with a relatively small amount of guide data, but the amount of guide data is still large;
[0121] Then use item 3 (diagnosis (coronary heart disease)) to screen the second set to obtain the third set with smaller guideline data, among which, the guideline data can be accurately obtained: ① blood pressure control standard (<150 / 90mmHg), ② Heart rate control standard (55-70 beats / min), ③ LDL-C control standard (1-...
example 2
[0129] Example 2: Structured patient B's medical information forms n pieces of information containing:
[0130] 1. Gender (female)
[0131] 2. Age (40 years old)
[0132] 3. Diagnosis (atrial fibrillation)
[0133] 4. Treatment method (drug: warfarin)
[0134] 5. Medication status (began to take it on April 15, 2020, and have taken it for a full month)
[0135] The first collection with a large amount of guideline data is obtained by screening the guideline database with article 1 (gender (female));
[0136] Then use the second item (age (40 years old)) to filter the first set to obtain the second set with a relatively small amount of guide data, but the amount of guide data is still large;
[0137] Then use item 3 (diagnosis (atrial fibrillation)) to screen the second set to obtain a third set with smaller guideline data, in which guideline data can be accurately obtained: ① blood pressure control standard (<140 / 90mmHg), ② Heart rate control standard (60-80 beats / min), ③...
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