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Artificial Intelligence (AI) approach to identifying factors that determine systolic blood pressure in type 2
Rodhan Khthir1, Prasanna Santhanam2
1Endocrinology Division, Sanford Health and University of North Dakota, School of Medicine, Bismarck, ND, 58501, USA.
Background And Aims:
Artificial Intelligence (AI) methods have recently become critical for research in diabetes in the era of big-data science.
Methods:
In this study, we used the data from the LOOK AHEAD and applied Random Forest to examine the factors determining SBP in persons with diabetes using the software R (version 4.0.3).
Results:
Our analysis (that included 4723 participants) showed that maximal exercise capacity, age, albumin to creatinine ratio, and serum creatinine were the key variables that determined systolic blood pressure.
Conclusions:
Maximum exercise capacity is an important predictor of systolic blood pressure in patients with type 2 diabetes.
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