AIMC Topic: Adult

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Association of Cardiovascular Mortality and Deep Learning-Funduscopic Atherosclerosis Score derived from Retinal Fundus Images.

American journal of ophthalmology
PURPOSE: The prediction of atherosclerosis using retinal fundus images and deep learning has not been shown possible. The purpose of this study was to develop a deep learning model which predicted atherosclerosis by using retinal fundus images and to...

Food Liking-Based Diet Quality Indexes (DQI) Generated by Conceptual and Machine Learning Explained Variability in Cardiometabolic Risk Factors in Young Adults.

Nutrients
The overall pattern of a diet (diet quality) is recognized as more important to health and chronic disease risk than single foods or food groups. Indexes of diet quality can be derived theoretically from evidence-based recommendations, empirically fr...

Robot-Driven Locomotor Perturbations Reveal Synergy-Mediated, Context-Dependent Feedforward and Feedback Mechanisms of Adaptation.

Scientific reports
Humans respond to mechanical perturbations that affect their gait by changing their motor control strategy. Previous work indicates that adaptation during gait is context dependent, and perturbations altering long-term stability are compensated for e...

Detection of tumors on brain MRI images using the hybrid convolutional neural network architecture.

Medical hypotheses
Brain tumor is one of the dangerous and deadly cancer types seen in adults and children. Early and accurate diagnosis of brain tumor is important for the treatment process. It is an important step for specialists to detect the brain tumor using compu...

Human vs. machine: the psychological and behavioral consequences of being compared to an outperforming artificial agent.

Psychological research
While artificial agents (AA) such as Artificial Intelligence are being extensively developed, a popular belief that AA will someday surpass human intelligence is growing. The present research examined whether this common belief translates into negati...

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury.

Journal of clinical epidemiology
OBJECTIVE: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury.

Will machine learning applied to neuroimaging in bipolar disorder help the clinician? A critical review and methodological suggestions.

Bipolar disorders
OBJECTIVES: The existence of anatomofunctional brain abnormalities in bipolar disorder (BD) is now well established by magnetic resonance imaging (MRI) studies. To create diagnostic and prognostic tools, as well as identifying biologically valid subt...

A biarticular passive exosuit to support balance control can reduce metabolic cost of walking.

Bioinspiration & biomimetics
Nowadays, the focus on the development of assistive devices just for people with mobility disorders has shifted towards enhancing physical abilities of able-bodied humans. As a result, the interest in the design of cheap and soft wearable exoskeleton...

Voice analysis in adductor spasmodic dysphonia: Objective diagnosis and response to botulinum toxin.

Parkinsonism & related disorders
INTRODUCTION: Adductor-type spasmodic dysphonia is a task-specific focal dystonia characterized by involuntary laryngeal muscle spasms. Due to the lack of quantitative instrumental tools, voice assessment in patients with adductor-type spasmodic dysp...