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Application of artificial intelligence in wearable devices: Opportunities and challenges
Background and objectives: Wearable technologies have added completely new and fast
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
Designing interpretable ML system to enhance trust in healthcare: A systematic review to proposed responsible clinician-AI-collaboration framework
Background Artificial intelligence (AI)-based medical devices and digital health
technologies, including medical sensors, wearable health trackers, telemedicine, mobile …
technologies, including medical sensors, wearable health trackers, telemedicine, mobile …
Efficient medical diagnosis of human heart diseases using machine learning techniques with and without GridSearchCV
Predicting cardiac disease is considered one of the most challenging tasks in the medical
field. It takes a lot of time and effort to figure out what's causing this, especially for doctors …
field. It takes a lot of time and effort to figure out what's causing this, especially for doctors …
Heart disease identification method using machine learning classification in e-healthcare
Heart disease is one of the complex diseases and globally many people suffered from this
disease. On time and efficient identification of heart disease plays a key role in healthcare …
disease. On time and efficient identification of heart disease plays a key role in healthcare …
Effective class-imbalance learning based on SMOTE and convolutional neural networks
Imbalanced Data (ID) is a problem that deters Machine Learning (ML) models from
achieving satisfactory results. ID is the occurrence of a situation where the quantity of the …
achieving satisfactory results. ID is the occurrence of a situation where the quantity of the …
[HTML][HTML] Graph-based relevancy-redundancy gene selection method for cancer diagnosis
Nowadays, microarray data processing is one of the most important applications in
molecular biology for cancer diagnosis. A major task in microarray data processing is gene …
molecular biology for cancer diagnosis. A major task in microarray data processing is gene …
Prediction of heart disease and classifiers' sensitivity analysis
Background Heart disease (HD) is one of the most common diseases nowadays, and an
early diagnosis of such a disease is a crucial task for many health care providers to prevent …
early diagnosis of such a disease is a crucial task for many health care providers to prevent …
Coronary artery disease detection using artificial intelligence techniques: A survey of trends, geographical differences and diagnostic features 1991–2020
While coronary angiography is the gold standard diagnostic tool for coronary artery disease
(CAD), but it is associated with procedural risk, it is an invasive technique requiring arterial …
(CAD), but it is associated with procedural risk, it is an invasive technique requiring arterial …
Ensemble of heterogeneous classifiers for diagnosis and prediction of coronary artery disease with reduced feature subset
Abstract Background and Objective: Coronary artery disease (CAD) is considered one of the
most prominent health issues causing high mortality in the world population. Hence, earlier …
most prominent health issues causing high mortality in the world population. Hence, earlier …
Prognosis prediction in traumatic brain injury patients using machine learning algorithms
Predicting treatment outcomes in traumatic brain injury (TBI) patients is challenging
worldwide. The present study aimed to achieve the most accurate machine learning (ML) …
worldwide. The present study aimed to achieve the most accurate machine learning (ML) …