AIMC Topic: Blood Pressure
Clear Filters Showing 51 to 60 of 274 articles
Deep Survival Analysis With Latent Clustering and Contrastive Learning.
IEEE journal of biomedical and health informatics
May 6, 2024
Survival analysis is employed to analyze the time before the event of interest occurs, which is broadly applied in many fields. The existence of censored data with incomplete supervision information about survival outcomes is one key challenge in sur...
Use of an Artificial Intelligence Device for Evaluating Blood Loss in Complex Major Orthopaedic Surgery Procedures.
The Journal of arthroplasty
May 3, 2024
BACKGROUND: An artificial intelligence algorithm that analyzes the pulse oximeter waveform in the fingertip can be used to determine the compensatory reserve index (CRI) in trauma patients. This measurement shows the remaining cardiovascular capacity...
Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning.
Diabetes & metabolism journal
Apr 30, 2024
BACKGRUOUND: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receive...
Artificial Intelligence-Derived Risk Prediction: A Novel Risk Calculator Using Office and Ambulatory Blood Pressure.
Hypertension (Dallas, Tex. : 1979)
Apr 25, 2024
BACKGROUND: Quantification of total cardiovascular risk is essential for individualizing hypertension treatment. This study aimed to develop and validate a novel, machine-learning-derived model to predict cardiovascular mortality risk using office bl...
The association between PM components and blood pressure changes in late pregnancy: A combined analysis of traditional and machine learning models.
Environmental research
Apr 3, 2024
BACKGROUND: PM is a harmful mixture of various chemical components that pose a challenge in determining their individual and combined health effects due to multicollinearity issues with traditional linear regression models. This study aimed to develo...
Mechanistic Assessment of Cardiovascular State Informed by Vibroacoustic Sensors.
Sensors (Basel, Switzerland)
Mar 29, 2024
Monitoring blood pressure, a parameter closely related to cardiovascular activity, can help predict imminent cardiovascular events. In this paper, a novel method is proposed to customize an existing mechanistic model of the cardiovascular system thro...
Prediction of cardiovascular and renal risk among patients with apparent treatment-resistant hypertension in the United States using machine learning methods.
Journal of clinical hypertension (Greenwich, Conn.)
Mar 24, 2024
Apparent treatment-resistant hypertension (aTRH), defined as blood pressure (BP) that remains uncontrolled despite unconfirmed concurrent treatment with three antihypertensives, is associated with an increased risk of developing cardiovascular and re...
A Survey on Blood Pressure Measurement Technologies: Addressing Potential Sources of Bias.
Sensors (Basel, Switzerland)
Mar 7, 2024
Regular blood pressure (BP) monitoring in clinical and ambulatory settings plays a crucial role in the prevention, diagnosis, treatment, and management of cardiovascular diseases. Recently, the widespread adoption of ambulatory BP measurement devices...
Development of a machine learning-based model for predicting individual responses to antihypertensive treatments.
Nutrition, metabolism, and cardiovascular diseases : NMCD
Mar 4, 2024
BACKGROUND AND AIMS: Personalized antihypertensive drug selection is essential for optimizing hypertension management. The study aimed to develop a machine learning (ML) model to predict individual blood pressure (BP) responses to different antihyper...
Transforming the cardiometabolic disease landscape: Multimodal AI-powered approaches in prevention and management.
Cell metabolism
Feb 29, 2024
The rise of artificial intelligence (AI) has revolutionized various scientific fields, particularly in medicine, where it has enabled the modeling of complex relationships from massive datasets. Initially, AI algorithms focused on improved interpreta...
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