AIMC Topic: Adult

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A Battery-Powered Ankle Exoskeleton Improves Gait Mechanics in a Feasibility Study of Individuals with Cerebral Palsy.

Annals of biomedical engineering
Neuromuscular impairment associated with cerebral palsy (CP) often leads to life-long walking deficits. Our goal was to evaluate the ability of a novel untethered wearable ankle exoskeleton to reduce the severity of gait pathology from CP. In this cl...

Development and Validation of a Deep Learning-Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs.

JAMA network open
IMPORTANCE: Interpretation of chest radiographs is a challenging task prone to errors, requiring expert readers. An automated system that can accurately classify chest radiographs may help streamline the clinical workflow.

Assessment of a Deep Learning Model Based on Electronic Health Record Data to Forecast Clinical Outcomes in Patients With Rheumatoid Arthritis.

JAMA network open
IMPORTANCE: Knowing the future condition of a patient would enable a physician to customize current therapeutic options to prevent disease worsening, but predicting that future condition requires sophisticated modeling and information. If artificial ...

Scoring upper-extremity motor function from EEG with artificial neural networks: a preliminary study.

Journal of neural engineering
OBJECTIVE: Motor function of chronic stroke survivors is generally accessed using clinical motor assessments. These motor assessments are partially subjective and require prior training for the examiners. Additionally, those motor function assessment...

Accurate Patient-Specific Machine Learning Models of Glioblastoma Invasion Using Transfer Learning.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: MR imaging-based modeling of tumor cell density can substantially improve targeted treatment of glioblastoma. Unfortunately, interpatient variability limits the predictive ability of many modeling approaches. We present a tran...

Predicting blood pressure from physiological index data using the SVR algorithm.

BMC bioinformatics
BACKGROUND: Blood pressure diseases have increasingly been identified as among the main factors threatening human health. How to accurately and conveniently measure blood pressure is the key to the implementation of effective prevention and control m...

Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke.

PloS one
BACKGROUND AND PURPOSE: This project assessed performance of natural language processing (NLP) and machine learning (ML) algorithms for classification of brain MRI radiology reports into acute ischemic stroke (AIS) and non-AIS phenotypes.

Movement time and guidance accuracy in teleoperation of robotic vehicles.

Ergonomics
Two experiments are reported on the steering of a tracked vehicle through straight-line courses and corners to determine the relationships between movement time and control accuracy with the geometry of the course, such as the vehicle width, the trac...

Functional brain networks and neuroanatomy underpinning nausea severity can predict nausea susceptibility using machine learning.

The Journal of physiology
KEY POINTS: Nausea is an adverse experience characterised by alterations in autonomic and cerebral function. Susceptibility to nausea is difficult to predict, but machine learning has yet to be applied to this field of study. The severity of nausea t...

Non-invasive machine learning estimation of effort differentiates sleep-disordered breathing pathology.

Physiological measurement
OBJECTIVE: Obstructive sleep-disordered breathing (SDB) events, unlike central events, are associated with increased respiratory effort. Esophageal pressure (P ) monitoring is the gold standard for measuring respiratory effort, but it is typically po...