AIMC Topic: Adult

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Prognostic factors of Rapid symptoms progression in patients with newly diagnosed parkinson's disease.

Artificial intelligence in medicine
Tracking symptoms progression in the early stages of Parkinson's disease (PD) is a laborious endeavor as the disease can be expressed with vastly different phenotypes, forcing clinicians to follow a multi-parametric approach in patient evaluation, lo...

Positive Emotions, More Than Anxiety or Other Negative Emotions, Predict Willingness to Interact With Robots.

Personality & social psychology bulletin
Like early work on human intergroup interaction, previous research on people's willingness to interact with robots has focused mainly on effects of anxiety. However, existing findings suggest that other negative emotions as well as some positive emot...

Factors affecting trust in high-vulnerability human-robot interaction contexts: A structural equation modelling approach.

Applied ergonomics
The current research proposed and tested a structural equation model (SEM) that describes hypothesized relationships among factors affecting trust in human-robot interaction (HRI) such as trustworthiness, human-likeness, intelligence, perfect automat...

The Role of Robotic Path Assistance and Weight Support in Facilitating 3D Movements in Individuals With Poststroke Hemiparesis.

Neurorehabilitation and neural repair
. High-intensity repetitive training is challenging to provide poststroke. Robotic approaches can facilitate such training by unweighting the limb and/or by improving trajectory control, but the extent to which these types of assistance are necessary...

Recognition of Negative Emotion using Long Short-Term Memory with Bio-Signal Feature Compression.

Sensors (Basel, Switzerland)
Negative emotion is one reason why stress causes negative feedback. Therefore, many studies are being done to recognize negative emotions. However, emotion is difficult to classify because it is subjective and difficult to quantify. Moreover, emotion...

Development and validation of machine learning models to predict gastrointestinal leak and venous thromboembolism after weight loss surgery: an analysis of the MBSAQIP database.

Surgical endoscopy
BACKGROUND: Postoperative gastrointestinal leak and venous thromboembolism (VTE) are devastating complications of bariatric surgery. The performance of currently available predictive models for these complications remains wanting, while machine learn...

A Deep Neural Network Application for Improved Prediction of [Formula: see text] in Type 1 Diabetes.

IEEE journal of biomedical and health informatics
[Formula: see text] is a primary marker of long-term average blood glucose, which is an essential measure of successful control in type 1 diabetes. Previous studies have shown that [Formula: see text] estimates can be obtained from 5-12 weeks of dail...

Ambivert degree identifies crucial brain functional hubs and improves detection of Alzheimer's Disease and Autism Spectrum Disorder.

NeuroImage. Clinical
Functional modules in the human brain support its drive for specialization whereas brain hubs act as focal points for information integration. Brain hubs are brain regions that have a large number of both within and between module connections. We arg...

Improving the detection of autism spectrum disorder by combining structural and functional MRI information.

NeuroImage. Clinical
Autism Spectrum Disorder (ASD) is a brain disorder that is typically characterized by deficits in social communication and interaction, as well as restrictive and repetitive behaviors and interests. During the last years, there has been an increase i...