HIGHLIGHTS
SUMMARY
Health and medical data in a primary care setting were utilized to facilitate the practical implementation of the risk assessment model for residents in primary care. The most intractable problem is that most of these models are targeted at patients in a hospital setting; thus, the data input into the models are all extracted from the EHRs of hospitals, which may not be readily available in primary care settings and suitable for general practitioners to implement. Highly precise risk prediction models for future hypertension were constructed using artificial_intelligence techniques in Japan. Health check-up . . .
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