[HTML][HTML] A review of machine learning in hypertension detection and blood pressure estimation based on clinical and physiological data
The use of machine learning techniques in medicine has increased in recent years due to a
rise in publicly available datasets. These techniques have been applied in high blood …
rise in publicly available datasets. These techniques have been applied in high blood …
Artificial intelligence in hypertension management: an ace up your sleeve
Arterial hypertension (AH) is a progressive issue that grows in importance with the increased
average age of the world population. The potential role of artificial intelligence (AI) in its …
average age of the world population. The potential role of artificial intelligence (AI) in its …
Identification of risk factors associated with obesity and overweight—a machine learning overview
A Chatterjee, MW Gerdes, SG Martinez - Sensors, 2020 - mdpi.com
Social determining factors such as the adverse influence of globalization, supermarket
growth, fast unplanned urbanization, sedentary lifestyle, economy, and social position slowly …
growth, fast unplanned urbanization, sedentary lifestyle, economy, and social position slowly …
[HTML][HTML] A new machine learning method for predicting systolic and diastolic blood pressure using clinical characteristics
A Shrivastava, M Chakkaravarthy, MA Shah - Healthcare Analytics, 2023 - Elsevier
Hypertension describes elevated blood pressure, which significantly impacts cardiovascular
diseases. Typically, a sphygmomanometer, a cuff-like device, is used to measure a patient's …
diseases. Typically, a sphygmomanometer, a cuff-like device, is used to measure a patient's …
Hybrid prediction model for type 2 diabetes and hypertension using DBSCAN-based outlier detection, synthetic minority over sampling technique (SMOTE), and …
As the risk of diseases diabetes and hypertension increases, machine learning algorithms
are being utilized to improve early stage diagnosis. This study proposes a Hybrid Prediction …
are being utilized to improve early stage diagnosis. This study proposes a Hybrid Prediction …
[HTML][HTML] Ensemble learning model for diagnosing COVID-19 from routine blood tests
Background and objectives The pandemic of novel coronavirus disease 2019 (COVID-19)
has severely impacted human society with a massive death toll worldwide. There is an …
has severely impacted human society with a massive death toll worldwide. There is an …
Development of disease prediction model based on ensemble learning approach for diabetes and hypertension
Early diseases prediction plays an important role for improving healthcare quality and can
help individuals avoid dangerous health situations before it is too late. This paper proposes …
help individuals avoid dangerous health situations before it is too late. This paper proposes …
Predicting hypertension using machine learning: Findings from Qatar Biobank Study
LA AlKaabi, LS Ahmed, MF Al Attiyah… - Plos one, 2020 - journals.plos.org
Background and objective Hypertension, a global burden, is associated with several risk
factors and can be treated by lifestyle modifications and medications. Prediction and early …
factors and can be treated by lifestyle modifications and medications. Prediction and early …
Artificial intelligence in preventive cardiology
Artificial intelligence (AI) is a field of study that strives to replicate aspects of human
intelligence into machines. Preventive cardiology, a subspeciality of cardiovascular (CV) …
intelligence into machines. Preventive cardiology, a subspeciality of cardiovascular (CV) …
A non-invasive continuous blood pressure estimation approach based on machine learning
S Chen, Z Ji, H Wu, Y Xu - Sensors, 2019 - mdpi.com
Considering the existing issues of traditional blood pressure (BP) measurement methods
and non-invasive continuous BP measurement techniques, this study aims to establish the …
and non-invasive continuous BP measurement techniques, this study aims to establish the …