Latest AI and machine learning research in strokes for healthcare professionals.
Untethered small-scale robots offer great promise for medical applications in complex biological env...
Atrial fibrillation (AF) is the most common supraventricular cardiac arrhythmia, resulting in high m...
A 76-year-old lady was found on the floor following a fall at home. She was uninjured, but unable to...
OBJECTIVE: This study aimed to develop and validate a machine learning-based short measure to assess...
Atrial fibrillation (AF) is the most common arrhythmia and is associated with increased thromboembo...
Coronavirus disease 2019 is a global health threat often accompanied with coagulopathy. Despite use...
INTRODUCTION: In elderly patients with cervical spinal cord injury, comorbidities such as cardiovasc...
Stroke poses an immense public health burden and remains among the primary causes of death and disab...
PURPOSE: To observe the effect of a brain-computer interface-operated lower limb rehabilitation robo...
OBJECTIVE: To evaluate the existing evidence of a machine learning-based classification system that ...
Warfarin remains the most widely prescribed oral anticoagulant in sub-Saharan Africa. However, becau...
This study outlines and developed a multilayer perceptron (MLP) neural network model for adolescent ...
Stroke is one of the most common neural disorders, which causes physical disabilities and motor impa...
This work was aimed to explore the role of CT angiography information provided by deep learning algo...
Conditional Random Fields (CRFs) are often used to improve the output of an initial segmentation mod...
Traditional approach for predicting coronary artery disease (CAD) is based on demographic data, symp...
BACKGROUND: The death due to stroke is caused by embolism of the arteries which is due to the ruptur...
Abnormal spasticity and associated synergistic patterns are the most common neuromuscular impairment...
PURPOSE: Rapid detection and vascular territorial classification of stroke enable the determination ...
To discuss the application method and effect of COPD patients in deep learning in intelligent monito...
Background Conventional prognostic scores usually require predefined clinical variables to predict o...