An intelligent health monitoring and diagnosis system based on the internet of things and fuzzy logic for cardiac arrhythmia COVID-19 patients
Background: During the COVID-19 pandemic, there is a global demand for intelligent health
surveillance and diagnosis systems for patients with critical conditions, particularly those …
surveillance and diagnosis systems for patients with critical conditions, particularly those …
Clinical and laboratory approach to diagnose COVID-19 using machine learning
Abstract Coronavirus 2 (SARS-CoV-2), often known by the name COVID-19, is a type of
acute respiratory syndrome that has had a significant influence on both economy and health …
acute respiratory syndrome that has had a significant influence on both economy and health …
Assessing transmission excellence and flow detection based on Machine Learning
A Suresh, R Kishorekumar, MS Kumar… - Optical and Quantum …, 2022 - Springer
Excellence in transmission can be assessed in optical transport networks before providing
any additional connections or upgrading the connections. Generally, the Physical Layer …
any additional connections or upgrading the connections. Generally, the Physical Layer …
Cloud-based deep learning-assisted system for diagnosis of sports injuries
X Wu, J Zhou, M Zheng, S Chen, D Wang… - Journal of Cloud …, 2022 - Springer
At both clinical and diagnostic levels, machine learning technologies could help facilitate
medical decision-making. Prediction of sports injuries, for instance, is a key component of …
medical decision-making. Prediction of sports injuries, for instance, is a key component of …
A Review of Machine Learning Algorithms and Feature Selection Techniques for Cardiovascular Disease Prediction: Insights and Implications
Cardiovascular disease (CVD) is a formidable public health challenge across the globe and
is the most prevalent cause of mortality. Early detection and accurate prediction of CVD can …
is the most prevalent cause of mortality. Early detection and accurate prediction of CVD can …
Exposomics and Cardiovascular Diseases: A Scoping Review of Machine Learning Approaches
Cardiovascular disease has been established as the world's number one killer, causing over
20 million deaths per year. This fact, along with the growing awareness of the impact of …
20 million deaths per year. This fact, along with the growing awareness of the impact of …
Development of nonlaboratory-based risk prediction models for cardiovascular diseases using conventional and machine learning approaches
Criticism of the implementation of existing risk prediction models (RPMs) for cardiovascular
diseases (CVDs) in new populations motivates researchers to develop regional models. The …
diseases (CVDs) in new populations motivates researchers to develop regional models. The …
A machine learning approach to cardiovascular disease prediction with advanced feature selection
A Abdullahi, M Ali Barre… - Indonesian Journal of …, 2024 - repository.simad.edu.so
Cardiovascular diseases (CVDs) pose a significant global public health challenge,
necessitating precise risk assessment for proactive treatment and optimal utilization of …
necessitating precise risk assessment for proactive treatment and optimal utilization of …
Exploration of Black Boxes of Supervised Machine Learning Models: A Demonstration on Development of Predictive Heart Risk Score
Machine learning (ML) often provides applicable high‐performance models to facilitate
decision‐makers in various fields. However, this high performance is achieved at the …
decision‐makers in various fields. However, this high performance is achieved at the …