Artificial Intelligence (AI) approach to identifying factors that determine systolic blood pressure in type 2 diabetes (study from the LOOK AHEAD cohort)-Reference-Cited by-同舟云学术

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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)

Published:2021-11 Issue:6 Volume:15 Page:102278
ISSN:1871-4021
Container-title:Diabetes & Metabolic Syndrome: Clinical Research & Reviews
language:en
Short-container-title:Diabetes & Metabolic Syndrome: Clinical Research & Reviews

Author:

Khthir Rodhan^ORCID,Santhanam Prasanna^ORCID

Funder

National Institute on Minority Health and Health Disparities

National Institute of Nursing Research

National Institute of Diabetes and Digestive and Kidney Diseases

Centers for Disease Control and Prevention

National Heart, Lung, and Blood Institute

Office of Research on Women's Health

Publisher

Elsevier BV

Subject

General Medicine,Endocrinology, Diabetes and Metabolism,Internal Medicine

Reference20 articles.

1. Blood pressure control in type 2 diabetic patients;Grossman;Cardiovasc Diabetol,2017

2. Systolic blood pressure response in SPRINT (systolic blood pressure intervention trial) and accord (action to control cardiovascular risk in diabetes): a possible explanation for discordant trial results;Huang;Journal of the American Heart Association,2017

3. Reaching an ACCORD on glycemia and systolic blood pressure targets in type 2 diabetes mellitus;MacDonald;Journal of the American Heart Association,2018

4. Systolic blood pressure response to exercise in type 1 diabetes families compared with healthy control individuals;Matteucci;J Hypertens,2006

5. Machine learning and blood pressure;Santhanam;J Clin Hypertens,2019

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Revolutionizing Cardiology through Artificial Intelligence—Big Data from Proactive Prevention to Precise Diagnostics and Cutting-Edge Treatment—A Comprehensive Review of the Past 5 Years;Diagnostics;2024-05-26

2. A New Era in Cardiometabolic Management: Unlocking the Potential of Artificial Intelligence for Improved Patient Outcomes;Endocrine Practice;2023-09

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