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[HTML][HTML] A survey of internet of medical things: technology, application and future directions
P He, D Huang, D Wu, H He, Y Wei, Y Cui… - Digital Communications …, 2024 - Elsevier
As the healthcare industry continues to embrace digital transformation, the Internet of
Medical Things (IoMT) emerges as a key technology. IoMT plays a critical role in …
Medical Things (IoMT) emerges as a key technology. IoMT plays a critical role in …
XAI Unveiled: Revealing the Potential of Explainable AI in Medicine-A Systematic Review
Nowadays, artificial intelligence in medicine plays a leading role. This necessitates the need
to ensure that artificial intelligence systems are not only high-performing but also …
to ensure that artificial intelligence systems are not only high-performing but also …
An interpretable neural network for outcome prediction in traumatic brain injury
Abstract Background Traumatic Brain Injury (TBI) is a common condition with potentially
severe long-term complications, the prediction of which remains challenging. Machine …
severe long-term complications, the prediction of which remains challenging. Machine …
A Comparison of Interpretable Machine Learning Approaches to Identify Outpatient Clinical Phenotypes Predictive of First Acute Myocardial Infarction
Background: Acute myocardial infarctions are deadly to patients and burdensome to
healthcare systems. Most recorded infarctions are patients' first, occur out of the hospital …
healthcare systems. Most recorded infarctions are patients' first, occur out of the hospital …
Predicting need for heart failure advanced therapies using an interpretable tropical geometry-based fuzzy neural network
Background Timely referral for advanced therapies (ie, heart transplantation, left ventricular
assist device) is critical for ensuring optimal outcomes for heart failure patients. Using …
assist device) is critical for ensuring optimal outcomes for heart failure patients. Using …
Learning Physiological Mechanisms that Predict Adverse Cardiovascular Events in Intensive Care Patients with Chronic Heart Disease
Chronic heart disease is a burdensome, complex, and fatal condition. Learning the
mechanisms driving the development of heart disease is key to early risk assessment and …
mechanisms driving the development of heart disease is key to early risk assessment and …
CoxFNN: Interpretable machine learning method for survival analysis
Survival analysis plays a pivotal role in healthcare, particularly in analyzing time-to-event
data such as in disease progression, treatment efficacy, and drug development. Traditional …
data such as in disease progression, treatment efficacy, and drug development. Traditional …
Survival analysis of heart failure patients using advanced machine learning techniques
P Makam, G Janardhan - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
According to World health organization, the death rate due to cardiovascular Disease (CVD)
globally touches an estimate of 17.9 million every year. It became very significant for the …
globally touches an estimate of 17.9 million every year. It became very significant for the …
EvolveFNN: An interpretable framework for early detection using longitudinal electronic health record data
The extensive adoption of artificial intelligence in clinical decision support systems
necessitates a significant presence of ML models that clinicians can easily interpret …
necessitates a significant presence of ML models that clinicians can easily interpret …
[PDF][PDF] A Machine Learning-Driven Approach to Comprehensive Cardiac Assessment in Health Monitoring
CP Kagita - foundryjournal.net
Comprehensive Cardiac Assessment in Health Monitoring project introduces an innovative
health monitoring application designed for continuous heartbeat analysis using machine …
health monitoring application designed for continuous heartbeat analysis using machine …