[Retracted] Integration of Artificial Intelligence and Blockchain Technology in Healthcare and Agriculture
Over the last decade, the healthcare sector has accelerated its digitization and electronic
health records (EHRs). As information technology progresses, the notion of intelligent health …
health records (EHRs). As information technology progresses, the notion of intelligent health …
[HTML][HTML] A predictive analytics approach for stroke prediction using machine learning and neural networks
The negative impact of stroke in society has led to concerted efforts to improve the
management and diagnosis of stroke. With an increased synergy between technology and …
management and diagnosis of stroke. With an increased synergy between technology and …
Clinical risk score for predicting recurrence following a cerebral ischemic event
D Chaudhary, V Abedi, J Li, CM Schirmer… - Frontiers in …, 2019 - frontiersin.org
Introduction: Recurrent stroke has a higher rate of death and disability. A number of risk
scores have been developed to predict short-term and long-term risk of stroke following an …
scores have been developed to predict short-term and long-term risk of stroke following an …
Prediction of brain stroke using machine learning algorithms and deep neural network techniques
The brain is the human body's primary upper organ. Stroke is a medical disorder in which
the blood arteries in the brain are ruptured, causing damage to the brain. When the supply of …
the blood arteries in the brain are ruptured, causing damage to the brain. When the supply of …
Trends and challenges of wearable multimodal technologies for stroke risk prediction
We review in this paper the wearable-based technologies intended for real-time monitoring
of stroke-related physiological parameters. These measurements are undertaken to prevent …
of stroke-related physiological parameters. These measurements are undertaken to prevent …
Simulation of a machine learning enabled learning health system for risk prediction using synthetic patient data
A Chen, DO Chen - Scientific Reports, 2022 - nature.com
When enabled by machine learning (ML), Learning Health Systems (LHS) hold promise for
improving the effectiveness of healthcare delivery to patients. One major barrier to LHS …
improving the effectiveness of healthcare delivery to patients. One major barrier to LHS …
Machine learning-based wearable devices for smart healthcare application with risk factor monitoring
SA Alex, S Ponkamali, TR Andrew… - … Industrial 4.0 Systems …, 2022 - igi-global.com
The stroke is an important health burden around the world that occurs due to the block of
blood supply to the brain. The interruption of blood supply depends on either the sudden …
blood supply to the brain. The interruption of blood supply depends on either the sudden …
Dynamic Explanation Selection Towards Successful User-Decision Support with Explainable AI
This paper addresses the problem of how to select explanations for XAI (Explainable AI)-
based Intelligent Decision Support Systems (IDSSs). IDSSs have shown promise in …
based Intelligent Decision Support Systems (IDSSs). IDSSs have shown promise in …
Artificial intelligence: a shifting paradigm in cardio-cerebrovascular medicine
The future of healthcare is an organic blend of technology, innovation, and human
connection. As artificial intelligence (AI) is gradually becoming a go-to technology in …
connection. As artificial intelligence (AI) is gradually becoming a go-to technology in …
Multi-objective learning and explanation for stroke risk assessment in Shanxi province
Stroke is the leading cause of death in China (Zhou et al. in The Lancet, 2019). A dataset
from Shanxi Province is analyzed to predict the risk of patients at four states …
from Shanxi Province is analyzed to predict the risk of patients at four states …