AIMC Topic: Arterial Pressure
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Machine learning analysis of integrated ABP and PPG signals towards early detection of coronary artery disease.
Scientific reports
Mar 12, 2025
Every year, Coronary Artery Disease (CAD) claims lives of over a million people. CAD occurs when the coronary arteries, responsible for supplying oxygenated blood to the heart, get occluded due to plaque deposits on their inner walls. The most critic...
Deep reinforcement learning for multi-targets propofol dosing.
Journal of clinical monitoring and computing
Mar 6, 2025
The administration of propofol for sedation or general anesthesia presents challenges due to the complex relationship between patient factors and real-time physiological responses. This study explores the application of deep reinforcement learning (D...
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...
Diastolic Versus Systolic or Mean Intraoperative Hypotension as Predictive of Perioperative Myocardial Injury in a White-Box Machine-Learning Model.
Anesthesia and analgesia
Feb 20, 2025
BACKGROUND: Intraoperative hypotension (IOH) and tachycardia are associated with perioperative myocardial injury (PMI), and thereby increased postoperative mortality. Patients undergoing vascular surgery are specifically at risk of developing cardiac...
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...
Blood Pressure Estimation Using Explainable Deep-Learning Models Based on Photoplethysmography.
Anesthesia and analgesia
Dec 16, 2024
BACKGROUND: Due to their invasiveness, arterial lines are not typically used in routine monitoring, despite their superior responsiveness in hemodynamic monitoring and detecting intraoperative hypotension. To address this issue, noninvasive, continuo...
Robust modelling of arterial blood pressure reconstruction from photoplethysmography.
Scientific reports
Dec 5, 2024
Blood pressure is a crucial indicator of cardiovascular disease, and arterial blood pressure (ABP) waveforms contain information that reflects the cardiovascular status. We propose a novel deep-learning method that converts photoplethysmogram (PPG) s...
Intraoperative Hypotension Prediction: Current Methods, Controversies, and Research Outlook.
Anesthesia and analgesia
Oct 23, 2024
Intraoperative hypotension prediction has been increasingly emphasized due to its potential clinical value in reducing organ injury and the broad availability of large-scale patient datasets and powerful machine learning tools. Hypotension prediction...
A machine learning approach for computation of cardiovascular intrinsic frequencies.
PloS one
Oct 26, 2023
Analysis of cardiovascular waveforms provides valuable clinical information about the state of health and disease. The intrinsic frequency (IF) method is a recently introduced framework that uses a single arterial pressure waveform to extract physiol...
Non-invasive arterial blood pressure measurement and SpO estimation using PPG signal: a deep learning framework.
BMC medical informatics and decision making
Jul 21, 2023
BACKGROUND: Monitoring blood pressure and peripheral capillary oxygen saturation plays a crucial role in healthcare management for patients with chronic diseases, especially hypertension and vascular disease. However, current blood pressure measureme...
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