AIMC Topic: Hypertension
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Integrating large language models with human expertise for disease detection in electronic health records.
Computers in biology and medicine
Jun 1, 2025
OBJECTIVE: Electronic health records (EHR) are widely available to complement administrative data-based disease surveillance and healthcare performance evaluation. Defining conditions from EHR is labour-intensive and requires extensive manual labelli...
Comparison of machine learning models for predicting stroke risk in hypertensive patients: Lasso regression model, random forest model, Boruta algorithm model, and Boruta algorithm combined with Lasso regression model.
Medicine
May 30, 2025
The aim of this study was to compare the performance of 4 machine learning models-Lasso regression model, random forest model, Boruta algorithm model, and the Boruta algorithm combined with Lasso regression-in predicting stroke risk among hypertensiv...
Long Short-Term Memory Network for Accelerometer-Based Hypertension Classification.
Studies in health technology and informatics
May 15, 2025
This study investigates the application of a Long Short-Term Memory (LSTM) architecture for classifying hypertension using accelerometer data, specifically focusing on physical activity and sleep from the publicly available NHANES 2011-2012 dataset. ...
Identification of hypertension subtypes using microRNA profiles and machine learning.
European journal of endocrinology
Mar 27, 2025
OBJECTIVE: Hypertension is a major cardiovascular risk factor affecting about 1 in 3 adults. Although the majority of hypertension cases (∼90%) are classified as "primary hypertension" (PHT), endocrine hypertension (EHT) accounts for ∼10% of cases an...
Artificial Intelligence-Enhanced Electrocardiography for Prediction of Incident Hypertension.
JAMA cardiology
Mar 1, 2025
IMPORTANCE: Hypertension underpins significant global morbidity and mortality. Early lifestyle intervention and treatment are effective in reducing adverse outcomes. Artificial intelligence-enhanced electrocardiography (AI-ECG) has been shown to iden...
Integrating machine learning and human use experience to identify personalized pharmacotherapy in Traditional Chinese Medicine: a case study on resistant hypertension.
Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan
Feb 1, 2025
OBJECTIVE: To enhance the understanding of identifying personalized pharmacotherapy options in Traditional Chinese Medicine (TCM), and further support the registration of new TCM drugs.
Application of machine learning algorithms in predicting new onset hypertension: a study based on the China Health and Nutrition Survey.
Environmental health and preventive medicine
Jan 1, 2025
BACKGROUND: Hypertension is a serious chronic disease that can significantly lead to various cardiovascular diseases, affecting vital organs such as the heart, brain, and kidneys. Our goal is to predict the risk of new onset hypertension using machin...
Determinants of developing cardiovascular disease risk with emphasis on type-2 diabetes and predictive modeling utilizing machine learning algorithms.
Medicine
Dec 6, 2024
This research aims to enhance our comprehensive understanding of the influence of type-2 diabetes on the development of cardiovascular diseases (CVD) risk, its underlying determinants, and to construct precise predictive models capable of accurately ...
Primary care research on hypertension: A bibliometric analysis using machine-learning.
Medicine
Nov 22, 2024
Hypertension is one of the most important chronic diseases worldwide. Hypertension is a critical condition encountered frequently in daily life, forming a significant area of service in Primary Health Care (PHC), which healthcare professionals often ...
Bridging Gaps with Generative AI: Enhancing Hypertension Monitoring Through Patient and Provider Insights.
Studies in health technology and informatics
Aug 22, 2024
This study introduces a Generative Artificial Intelligence (GenAI) assistant designed to address key challenges in Remote Patient Monitoring (RPM) for hypertension. After a comprehensive needs assessment from clinicians and patients, we identified pi...
Natural Language Processing
Physician-Patient Relations
Telemedicine
Surveys and Questionnaires
Stakeholder Participation
Health Knowledge, Attitudes, Practice
Patient Participation
Humans
Hypertension
Digital Health
Monitoring, Physiologic
Physicians
Reproducibility of Results
Needs Assessment
Evidence Gaps
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