Latest AI and machine learning research in strokes for healthcare professionals.
Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the init...
This paper focus on a neural network classification model to estimate the association among gender, race, BMI, age, smoking, kidney disease and diabetes in hypertensive patients. It also shows that artificial neural network techniques applied to large clinical data sets may provide a meaningful data-driven approach to categorize patients for population health management, and support in the control...
Continuous blood pressure (BP) measurement is crucial for reliable and timely hypertension detection. State-of-the-art continuous BP measurement metho...
BACKGROUND: Stroke survivors often experience upper-limb motor deficits and achieve limited motor recovery within six months after the onset of stroke...
Ischemic stroke is a common neurological disorder, and is still the principal cause of serious long-term disability in the world. Selection of feature...
BACKGROUND: Low-molecular-weight heparins (LMWHs) are easily dialysable with high-flow membranes; however, it is not clear whether the LMWH dose shoul...
Accurate, automated extraction of clinical stroke information from unstructured text has several important applications. ICD-9/10 codes can misclassif...
Machine learning applications in cardiology have rapidly evolved in the past decade. With the availability of machine learning tools coupled with vast...
BACKGROUND: Atypical walking in the months and years after stroke constrain community reintegration and reduce mobility, health, and quality of life. ...
MOTIVATION: Machine learning (ML)-based stroke risk stratification systems have typically focused on conventional risk factors (CRF) (AtheroRisk-conve...
Functional electrical stimulation and robot-assisted gait training are techniques which are used in a clinical routine to enhance the rehabilitation p...
BACKGROUND: The rehabilitation of cognitive and behavioral abnormalities in individuals with stroke is essential for promoting patient's recovery and ...
Comorbidities such as anemia or hypertension and physiological factors related to exertion can influence a patient's hemodynamics and increase the sev...
BACKGROUND: Pregnant women with mechanical heart valves are at significant risk of obstetric/cardiac complications. This study compares the anticoagul...
Hypertension is a potentially unsafe health ailment, which can be indicated directly from the blood pressure (BP). Hypertension always leads to other ...
In this paper, we demonstrate the feasibility and performance of deep residual neural networks for volumetric segmentation of irreversibly damaged bra...
Most post-stroke patients experience upper limb functionality challenges. Emergent therapies using upper limb-based robot machines present opportuniti...
Current stroke risk assessment tools presume the impact of risk factors is linear and cumulative. However, both novel risk factors and their interplay...
New-era soft microrobots for biomedical applications need to mimic the essential structures and collective functions of creatures from nature. Biocomp...
A robot-assisted hand is used for the rehabilitation of patients with impaired upper limb function, particularly for stroke patients with a loss of mo...