AIMC Topic: Hypertension

Clear Filters Showing 211 to 220 of 261 articles

A prediction model of blood pressure for telemedicine.

Health informatics journal
This paper presents a new study based on a machine learning technique, specifically an artificial neural network, for predicting systolic blood pressure through the correlation of variables (age, BMI, exercise level, alcohol consumption level, smokin...

Hypertension, haematuria and renal functioning in haemophilia - a cross-sectional study in Europe.

Haemophilia : the official journal of the World Federation of Hemophilia
BACKGROUND AND OBJECTIVES: This cross-sectional, epidemiological study sought to assess the prevalence and extent of potential risk factors for hypertension, particularly renal function related to haematuria and their associations in people with haem...

Microarray expression profiling and gene ontology analysis of long non-coding RNAs in spontaneously hypertensive rats and their potential roles in the pathogenesis of hypertension.

Molecular medicine reports
Long non-coding RNAs (lncRNAs) have been demonstrated to be significant in numerous biological processes. Hypertension is a form of cardiovascular disease with at least one billion cases worldwide. The present study sought to compare the differential...

The advantages of combination therapy on hypertension: development of immediate release perindopril-indapamide tablet and assessment of bioequivalence studies.

Pharmaceutical development and technology
Hypertension has a major associated risk for organ damage and mortality, which is further heightened in patients with prior cardiovascular events, comorbid diabetes mellitus, microalbuminuria and renal impairment. Convers Plus tablet including perind...

Phase information of time-frequency transforms as a key feature for classification of atrial fibrillation episodes.

Physiological measurement
Patients suffering from atrial fibrillation can be classified into different subtypes, according to the temporal pattern of the arrhythmia and its recurrence. Nowadays, clinicians cannot differentiate a priori between the different subtypes, and pati...

Advanced prediction of heart failure risk in elderly diabetic and hypertensive patients using nine machine learning models and novel composite indices: insights from NHANES 2003-2016.

European journal of preventive cardiology
AIMS: As the global population ages, cardiovascular diseases, particularly heart failure (HF), have become leading causes of mortality and disability among elderly patients. Diabetes and hypertension are major risk factors for cardiovascular diseases...

Machine learning-based analyses of contributing factors for the development of hypertension: a comparative study.

Clinical and experimental hypertension (New York, N.Y. : 1993)
OBJECTIVES: Sufficient attention has not been given to machine learning (ML) models using longitudinal data for investigating important predictors of new onset of hypertension. We investigated the predictive ability of several ML models for the devel...

The non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) as predictors of hypertensive patients: Analyses of NHANES data with machine learning.

Medicine
Elevated values of the non-HDL/HDL cholesterol ratio (NHHR) have been associated with increased hypertension risk, indicating its potential as a pathogenic factor, but its assessment remains challenging. We analyzed data from 22,562 hypertensive part...

Machine Learning and Artificial Intelligence for Research on Hypertension.

American journal of hypertension
Hypertension continues to be the leading modifiable risk factor for mortality globally, contributing significantly to cardiovascular disease. The American Heart Association (AHA) 2017 Hypertension Guidelines define hypertension as blood pressure (BP)...

Artificial intelligence and digital twins for the personalised prediction of hypertension risk.

Computers in biology and medicine
Hypertension is a significant global health challenge, contributing substantially to morbidity and mortality through its association with various cardiovascular diseases. Traditional approaches to hypertension risk prediction, which rely on broad epi...