AIMC Topic: Young Adult
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Gait characteristics and clinical relevance of hereditary spinocerebellar ataxia on deep learning.
Artificial intelligence in medicine
Jan 7, 2020
BACKGROUND: Deep learning has always been at the forefront of scientific research. It has also been applied to medical research. Hereditary spinocerebellar ataxia (SCA) is characterized by gait abnormalities and is usually evaluated semi-quantitative...
Assessing various sensorimotor and cognitive functions in people with epilepsy is feasible with robotics.
Epilepsy & behavior : E&B
Jan 7, 2020
BACKGROUND: Epilepsy is a common neurological disorder characterized by recurrent seizures, along with comorbid cognitive and psychosocial impairment. Current gold standards of assessment can quantify cognitive and motor performance, but may not capt...
Fatigue Evaluation through Machine Learning and a Global Fatigue Descriptor.
Journal of healthcare engineering
Jan 7, 2020
Research in physiology and sports science has shown that fatigue, a complex psychophysiological phenomenon, has a relevant impact in performance and in the correct functioning of our motricity system, potentially being a cause of damage to the human ...
Teaching cross-cultural design thinking for healthcare.
Breast (Edinburgh, Scotland)
Jan 6, 2020
OBJECTIVES: Artificial intelligence (AI) is poised to transform breast cancer care. However, most scientists, engineers, and clinicians are not prepared to contribute to the AI revolution in healthcare. In this paper, we describe our experiences teac...
Real-time machine learning classification of pallidal borders during deep brain stimulation surgery.
Journal of neural engineering
Jan 6, 2020
OBJECTIVE: Deep brain stimulation (DBS) of the internal segment of the globus pallidus (GPi) in patients with Parkinson's disease and dystonia improves motor symptoms and quality of life. Traditionally, pallidal borders have been demarcated by electr...
Interpreting neural decoding models using grouped model reliance.
PLoS computational biology
Jan 6, 2020
Machine learning algorithms are becoming increasingly popular for decoding psychological constructs based on neural data. However, as a step towards bridging the gap between theory-driven cognitive neuroscience and data-driven decoding approaches, th...
Automated tracheal intubation in an airway manikin using a robotic endoscope: a proof of concept study.
Anaesthesia
Jan 3, 2020
Robotic endoscope-automated via laryngeal imaging for tracheal intubation (REALITI) has been developed to enable automated tracheal intubation. This proof-of-concept study using a convenience sample of participants, comprised of trained anaesthetists...
Accurate prediction of responses to transarterial chemoembolization for patients with hepatocellular carcinoma by using artificial intelligence in contrast-enhanced ultrasound.
European radiology
Jan 3, 2020
OBJECTIVES: We aimed to establish and validate an artificial intelligence-based radiomics strategy for predicting personalized responses of hepatocellular carcinoma (HCC) to first transarterial chemoembolization (TACE) session by quantitatively analy...
Automated CT registration tool improves sensitivity to change in ventricular volume in patients with shunts and drains.
The British journal of radiology
Jan 3, 2020
OBJECTIVE: CT is the mainstay imaging modality for assessing change in ventricular volume in patients with ventricular shunts or external ventricular drains (EVDs). We evaluated the performance of a novel fully automated CT registration and subtracti...
Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for the Prediction of Incident Atrial Fibrillation.
JAMA network open
Jan 3, 2020
IMPORTANCE: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, and its early detection could lead to significant improvements in outcomes through the appropriate prescription of anticoagulation medication. Although a variety of...
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