AIMC Topic: Stroke

Clear Filters Showing 981 to 990 of 1213 articles

Accuracy of Machine Learning in Predicting Post-Stroke Depression: A Systematic Review and Meta-Analysis.

Brain and behavior
INTRODUCTION: Post-stroke depression is one of the important complications of stroke and affects patients' quality of life. Early identification of post-stroke depression is crucial for its timely prevention. The accuracy of machine learning as a pre...

Identifying individuals at risk of post-stroke depression: Development and validation of a predictive model.

Saudi medical journal
OBJECTIVES: To identify the factors associated with post-stroke depression (PSD) and develop a machine learning predictive model using a large dataset, considering sociodemographic, lifestyle, and clinical factors.

Machine Learning Assisted Stroke Prediction in Mechanical Circulatory Support: Predictive Role of Systemic Mitochondrial Dysfunction.

ASAIO journal (American Society for Artificial Internal Organs : 1992)
Stroke continues to be a major adverse event in advanced congestive heart failure (CHF) patients after continuous-flow left ventricular assist device (CF-LVAD) implantation. Abnormalities in mitochondrial oxidative phosphorylation (OxPhos) have been ...

Evaluating Performance of a Deep Learning Multilabel Segmentation Model to Quantify Acute and Chronic Brain Lesions at MRI after Stroke and Predict Prognosis.

Radiology. Artificial intelligence
Purpose To develop and evaluate a multilabel deep learning network to identify and quantify acute and chronic brain lesions at multisequence MRI after acute ischemic stroke (AIS) and assess relationships between clinical and model-extracted radiologi...

Integrating Artificial Intelligence in Stroke Rehabilitation: Current Trends and Future Directions; A mini review.

JPMA. The Journal of the Pakistan Medical Association
Rehabilitation following a stroke faces challenges in offering customized treatment and attaining the best possible outcomes. The utilization of artificial intelligence (AI) presents transformative solutions that have the potential to revolutionize e...

Deep learning-based classification of speech disorder in stroke and hearing impairment.

PloS one
BACKGROUND AND OBJECTIVE: Speech disorders can arise from various causes, including congenital conditions, neurological damage, diseases, and other disorders. Traditionally, medical professionals have used changes in voice to diagnose the underlying ...

The use of artificial intelligence to identify ophthalmic biomarkers in cardiovascular disease and stroke: a narrative review.

Sao Paulo medical journal = Revista paulista de medicina
BACKGROUND: Cardiovascular disease (CVD) and stroke are among the leading causes of death worldwide.

Optimizing Stroke Detection Using Evidential Networks and Uncertainty-Based Refinement.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Evaluating neurological impairments post-stroke is essential for assessing treatment efficacy and managing subsequent disabilities. Conventional clinical assessment methods depend largely on clinicians' visual and physical evaluations, resulting in c...

Artificial Intelligence in Transcranial Doppler Ultrasonography.

Current medical imaging
Transcranial Doppler is an instrumental ultrasound method capable of providing data on various brain pathologies, in particular, the study of cerebral hemodynamics in stroke, quickly, economically, and with repeatability of the data themselves. Howev...

Predictive Value of Machine Learning Models for Cerebral Edema Risk in Stroke Patients: A Meta-Analysis.

Brain and behavior
INTRODUCTION: Stroke patients are at high risk of developing cerebral edema, which can have severe consequences. However, there are currently few effective tools for early identification or prediction of this risk. As machine learning (ML) is increas...