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Artificial Intelligence (AI) approach to identifying factors that determine systolic blood pressure in type 2 diabetes (study from the LOOK AHEAD cohort).
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- Author(s): Khthir R;Khthir R; Santhanam P; Santhanam P
- Source:
Diabetes & metabolic syndrome [Diabetes Metab Syndr] 2021 Nov-Dec; Vol. 15 (6), pp. 102278. Date of Electronic Publication: 2021 Sep 11.- Publication Type:
Journal Article- Language:
English - Source:
- Additional Information
- Source: Publisher: Elsevier Ltd Country of Publication: Netherlands NLM ID: 101462250 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1878-0334 (Electronic) Linking ISSN: 18714021 NLM ISO Abbreviation: Diabetes Metab Syndr Subsets: MEDLINE
- Publication Information: Original Publication: Amsterdam : Elsevier Ltd.
- Subject Terms: Artificial Intelligence* ; Blood Pressure*; Albumins/*analysis ; Biomarkers/*blood ; Creatinine/*blood ; Diabetes Mellitus, Type 2/*physiopathology ; Hypertension/*diagnosis; Adult ; Aged ; Blood Pressure Determination ; Exercise ; Female ; Follow-Up Studies ; Humans ; Hypertension/epidemiology ; Male ; Middle Aged ; Prognosis ; Randomized Controlled Trials as Topic ; United States/epidemiology
- Abstract: 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.
Competing Interests: Declaration of competing interest The author of the manuscript has no disclosures to make and report no conflict of interest.
(Copyright © 2021 Diabetes India. Published by Elsevier Ltd. All rights reserved.) - Contributed Indexing: Keywords: Artificial intelligence; Diabetes mellitus; Predictors; Systolic blood pressure
- Accession Number: 0 (Albumins)
0 (Biomarkers)
AYI8EX34EU (Creatinine) - Publication Date: Date Created: 20210925 Date Completed: 20220307 Latest Revision: 20220307
- Publication Date: 20221213
- Accession Number: 10.1016/j.dsx.2021.102278
- Accession Number: 34562867
- Source:
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