AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Recovery of Function

Showing 31 to 40 of 437 articles

Clear Filters

Role of Artificial Intelligence and Machine Learning to Create Predictors, Enhance Molecular Understanding, and Implement Purposeful Programs for Myocardial Recovery.

Methodist DeBakey cardiovascular journal
Heart failure (HF) affects millions of individuals and causes hundreds of thousands of deaths each year in the United States. Despite the public health burden, medical and device therapies for HF significantly improve clinical outcomes and, in a subs...

Predicting recovery following stroke: Deep learning, multimodal data and feature selection using explainable AI.

NeuroImage. Clinical
Machine learning offers great potential for automated prediction of post-stroke symptoms and their response to rehabilitation. Major challenges for this endeavour include the very high dimensionality of neuroimaging data, the relatively small size of...

Prognosticating global functional outcome in the recurrent ischemic stroke using baseline clinical and pre-clinical features: A machine learning study.

Journal of evaluation in clinical practice
BACKGROUND AND PURPOSE: Recurrent ischemic stroke (RIS) induces additional functional limitations in patients. Prognosticating globally functional outcome (GFO) in RIS patients is thereby important to plan a suitable rehabilitation programme. This st...

Development and External Validation of a Motor Intention-Integrated Prediction Model for Upper Extremity Motor Recovery After Intention-Driven Robotic Hand Training for Chronic Stroke.

Archives of physical medicine and rehabilitation
OBJECTIVE: To derive and validate a prediction model for minimal clinically important differences (MCIDs) in upper extremity (UE) motor function after intention-driven robotic hand training using residual voluntary electromyography (EMG) signals from...

Prediction of hearing recovery with deep learning algorithm in sudden sensorineural hearing loss.

Scientific reports
This study aimed to establish a deep learning-based predictive model for the prognosis of idiopathic sudden sensorineural hearing loss (SSNHL). Data from 1108 patients with SSNHL between January 2015 and May 2023 were retrospectively analyzed. Patien...

Center of Pressure- and Machine Learning-based Gait Score and Clinical Risk Factors for Predicting Functional Outcome in Acute Ischemic Stroke.

Archives of physical medicine and rehabilitation
OBJECTIVES: To investigate whether machine learning (ML)-based center of pressure (COP) analysis for gait assessment, when used in conjunction with clinical information, offers additive benefits in predicting functional outcomes in patients with acut...

Data-driven prediction of spinal cord injury recovery: An exploration of current status and future perspectives.

Experimental neurology
Spinal Cord Injury (SCI) presents a significant challenge in rehabilitation medicine, with recovery outcomes varying widely among individuals. Machine learning (ML) is a promising approach to enhance the prediction of recovery trajectories, but its i...

From data to decisions: AI and functional connectivity for diagnosis, prognosis, and recovery prediction in stroke.

GeroScience
Stroke is a severe medical condition which may lead to permanent disability conditions. The initial 8 weeks following a stroke are crucial for rehabilitation, as most recovery occurs during this period. Personalized approaches and predictive biomarke...

Machine-learning-based prediction by stacking ensemble strategy for surgical outcomes in patients with degenerative cervical myelopathy.

Journal of orthopaedic surgery and research
BACKGROUND: Machine learning (ML) is extensively employed for forecasting the outcome of various illnesses. The objective of the study was to develop ML based classifiers using a stacking ensemble strategy to predict the Japanese Orthopedic Associati...