Highly precise risk prediction model for new‐onset hypertension using artificial intelligence techniques-Reference-Cited by-同舟云学术

Highly precise risk prediction model for new‐onset hypertension using artificial intelligence techniques

Published:2019-12-09 Issue:3 Volume:22 Page:445-450
ISSN:1524-6175
Container-title:The Journal of Clinical Hypertension
language:en
Short-container-title:J Clin Hypertens

Author:

Kanegae Hiroshi¹²,Suzuki Kenji³,Fukatani Kyohei⁴,Ito Tetsuya⁴,Harada Nakahiro⁴,Kario Kazuomi¹^ORCID

Affiliation:

1. Department of Medicine Division of Cardiovascular Medicine Jichi Medical University School of Medicine Tochigi Japan

2. Genki Plaza Medical Center for Health Care Tokyo Japan

3. The Japan Health Promotion Foundation Tokyo Japan

4. Fukuda Denshi Co., Ltd. Tokyo Japan

Funder

Fukuda Denshi Co., Ltd.

Publisher

Wiley

Subject

Cardiology and Cardiovascular Medicine,Endocrinology, Diabetes and Metabolism,Internal Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jch.13759

Reference30 articles.

1. World Health Organization.Global health risks: mortality and burden of disease attributable to selected major risks.http://www.who.int/healthinfo/global_burden_disease/global_health_risks/en/. Accessed May 2 2019.

2. Hypertension and Dementia: A comprehensive review from the HOPE Asia Network

3. World Health Organization.A global brief on hypertension.http://www.who.int/cardiovascular_diseases/publications/global_brief_hypertension/en/. Accessed May 2 2019.

4. The Hypertension Prevention Trial: Three-Year Effects of Dietary Changes on Blood Pressure

5. Effects of weight loss and sodium reduction intervention on blood pressure and hypertension incidence in overweight people with high‐normal blood pressure. The trials of hypertension prevention, phase II. The trials of Hypertension Prevention Collaborative Research Group;Arch Intern Med,1997

Cited by 72 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. Acute Complication Prediction and Diagnosis Model CLSTM-BPR: A Fusion Method of Time Series Deep Learning and Bayesian Personalized Ranking;Tsinghua Science and Technology;2024-10

2. Predicting new cases of hypertension in Swedish primary care with a machine learning tool;Preventive Medicine Reports;2024-08

3. Digitalization of hypertension management: a paradigm shift;Naunyn-Schmiedeberg's Archives of Pharmacology;2024-06-15

4. Precise risk‐prediction model including arterial stiffness for new‐onset atrial fibrillation using machine learning techniques;The Journal of Clinical Hypertension;2024-06-08

5. Social acceptance of artificial intelligence (AI) application for improving medical service diagnostics;Human Technology;2024-05-27