BACKGROUND: Ventricular repolarisation is affected differently by the types of anaesthetics used. This study aimed to compare the effect of different types of anaesthetics on ventricular repolarisation during robot-assisted laparoscopic radical prost...
Continuous blood pressure (BP) measurement is crucial for reliable and timely hypertension detection. State-of-the-art continuous BP measurement methods based on pulse transit time or multiple parameters require simultaneous electrocardiogram (ECG) a...
Atrial fibrillation (AF) is a common cardiac disorder that can cause severe complications. AF diagnosis is typically based on the electrocardiogram (ECG) evaluation in hospitals or in clinical facilities. The aim of the present work is to propose a n...
BACKGROUND: Anaemia is an important health-care burden globally, and screening for anaemia is crucial to prevent multi-organ injury, irreversible complications, and life-threatening adverse events. We aimed to establish whether a deep learning algori...
We present performance results concerning the validation for anxiety level detection based on trained mathematical models using supervised machine learning techniques. The model training is based on biosignals acquired in a randomized controlled tria...
Emotional responses are associated with distinct body alterations and are crucial to foster adaptive responses, well-being, and survival. Emotion identification may improve peoples' emotion regulation strategies and interaction with multiple life con...
Electrocardiogram (ECG) signal is critical to the classification of cardiac arrhythmia using some machine learning methods. In practice, the ECG datasets are usually with multiple missing values due to faults or distortion. Unfortunately, many establ...
PURPOSE OF REVIEW: To (i) review the concept of artificial intelligence (AI); (ii) summarize recent developments in artificial intelligence-enabled electrocardiogram (AI-ECG); (iii) address notable inherent limitations and challenges of AI-ECG; and (...
Machine learning applications in cardiology have rapidly evolved in the past decade. With the availability of machine learning tools coupled with vast data sources, the management of atrial fibrillation (AF), a common chronic disease with significant...
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