This study presents an innovative approach to cuffless blood pressure prediction by integrating speech and demographic features. With a focus on non-invasive monitoring, especially in remote regions, our model harnesses speech signals and demographic...
BACKGROUND: The effect of renal impairment in patients who receive intravenous thrombolysis for acute ischemic stroke (AIS) is unclear. We aimed to determine the associations of renal impairment and clinical outcomes and any modification of the effec...
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...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Estimating blood pressure (BP) values from physiological signals (e.g., photoplethysmogram (PPG)) using deep learning models has recently received increased attention, yet challenges remain in terms of models' generalizability. Here, we propose takin...
The global prevalence of hypertension continues excessively elevated, especially among low- and middle-income nations. Workplaces provide tremendous opportunities as a unique, easily accessible and practical avenue for early diagnosis and treatment o...
Blood pressure (BP) is one of the most prominent indicators of potential cardiovascular disorders. Traditionally, BP measurement relies on inflatable cuffs, which is inconvenient and limit the acquisition of such important health-related information ...
This paper proposes the use of machine learning models to predict one's risk of having hypertension in the future using their routine health checkup data of their current and past visits to a health checkup center. The large-scale and high-dimensiona...
Gravity, an invisible but constant force , challenges the regulation of blood pressure when transitioning between postures. As physiological reserve diminishes with age, individuals grow more susceptible to such stressors over time, risking inadequat...
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...
With the rapid advancements in machine learning, its applications in the medical field have garnered increasing interest, particularly in non-invasive health monitoring methods. Blood pressure (BP) estimation using Photoplethysmogram (PPG) signals pr...
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