AIMC Topic: Blood Pressure Determination
Clear Filters Showing 1 to 10 of 104 articles
Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population.
Scientific reports
Jul 15, 2025
Monitoring of cardiac output (CO) is a mainstay of hemodynamic management in the acutely or critically ill patient. Invasive determination of CO using thermodilution, albeit regarded as the gold standard, is cumbersome and bears risks inherent to cat...
Evolving Blood Pressure Estimation: From Feature Analysis to Image-Based Deep Learning Models.
Journal of medical systems
Jul 9, 2025
Traditional cuffless blood pressure (BP) estimation methods often require collecting physiological signals, such as electrocardiogram (ECG) and photoplethysmography (PPG), from two distinct body sites to compute metrics like pulse transit time (PTT) ...
Cuff-less blood pressure monitoring via PPG signals using a hybrid CNN-BiLSTM deep learning model with attention mechanism.
Scientific reports
Jul 1, 2025
Blood pressure (BP) serves as a fundamental indicator of cardiovascular health, measuring the force exerted by circulating blood against arterial walls during each heartbeat. This paper introduces an advanced deep learning framework for precise, non-...
Cuffless Blood Pressure Measurement: Where Do We Actually Stand?
Hypertension (Dallas, Tex. : 1979)
Apr 15, 2025
Cuffless blood pressure (BP) measurement offers considerable potential for clinical practice but is a challenging technological field. Many are investigating pulse wave analysis with or without pulse arrival time in which machine learning is applied ...
Transfer Learning Enhanced Blood Pressure Monitoring Based on Flexible Optical Pulse Sensing Patch.
ACS sensors
Apr 15, 2025
Blood pressure (BP), a crucial health biomarker, is essential for detecting early indications of cardiovascular disease in routine monitoring and clinical surveillance of inpatients. However, conventional cuff-based BP measurements are limited in pro...
A spectral machine learning approach to derive central aortic pressure waveforms from a brachial cuff.
Proceedings of the National Academy of Sciences of the United States of America
Feb 26, 2025
Analyzing cardiac pulse waveforms offers valuable insights into heart health and cardiovascular disease risk, although obtaining the more informative measurements from the central aorta remains challenging due to their invasive nature and limited non...
A two-branch framework for blood pressure estimation using photoplethysmography signals with deep learning and clinical prior physiological knowledge.
Physiological measurement
Feb 7, 2025
This paper presents a novel dual-branch framework for estimating blood pressure (BP) using photoplethysmography (PPG) signals. The method combines deep learning with clinical prior knowledge and models different time periods (morning, afternoon, and ...
Artificial intelligence-based, non-invasive assessment of the central aortic pressure in adults after operative or interventional treatment of aortic coarctation.
Open heart
Jan 21, 2025
BACKGROUND: Aortic coarctation (CoA) is a congenital anomaly leading to upper-body hypertension and lower-body hypotension. Despite surgical or interventional treatment, arterial hypertension may develop and contribute to morbidity and mortality. Con...
Detecting anomalies in smart wearables for hypertension: a deep learning mechanism.
Frontiers in public health
Jan 15, 2025
INTRODUCTION: The growing demand for real-time, affordable, and accessible healthcare has underscored the need for advanced technologies that can provide timely health monitoring. One such area is predicting arterial blood pressure (BP) using non-inv...
rU-Net, Multi-Scale Feature Fusion and Transfer Learning: Unlocking the Potential of Cuffless Blood Pressure Monitoring With PPG and ECG.
IEEE journal of biomedical and health informatics
Jan 7, 2025
This study introduces an innovative deep-learning model for cuffless blood pressure estimation using PPG and ECG signals, demonstrating state-of-the-art performance on the largest clean dataset, PulseDB. The rU-Net architecture, a fusion of U-Net and...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31964
- Neural Networks, Computer 30201
- Algorithms 27375
- Deep Learning 26880
- Artificial Intelligence 24818
- Robotics 13382
- Image Processing, Computer-Assisted 9730
- Retrospective Studies 9328
- Magnetic Resonance Imaging 6341
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4863
- Support Vector Machine 4762
- Computational Biology 4328
- Brain 4125
- Computer Simulation 3932
Recent Journals
- Scientific reports 6689
- Sensors (Basel, Switzerland) 4794
- PloS one 4186
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1915
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1167
- Journal of chemical information and modeling 1059
- Nature communications 1029
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 872
- Journal of medical Internet research 853
- Briefings in bioinformatics 853