AIMC Topic: Adult

Clear Filters Showing 8541 to 8550 of 15606 articles

Design of a Robotic Coach for Motor, Social and Cognitive Skills Training Toward Applications With ASD Children.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Socially assistive robots may help the treatment of autism spectrum disorder(ASD), through games using dyadic interactions to train social skills. Existing systems are mainly based on simplified protocols which qualitatively evaluate subject performa...

Neuromate robot-assisted ventricular catheter insertion.

British journal of neurosurgery
BACKGROUND AND IMPORTANCE: Insertion of ventricular catheters into small ventricles may require image guidance. Several options exist, including ultrasound guidance, frameless, and frame-based stereotactic approaches. There is no literature on manage...

Augmented intelligence to predict 30-day mortality in patients with cancer.

Future oncology (London, England)
An augmented intelligence tool to predict short-term mortality risk among patients with cancer could help identify those in need of actionable interventions or palliative care services. An algorithm to predict 30-day mortality risk was developed us...

Nonlinear manifold learning in functional magnetic resonance imaging uncovers a low-dimensional space of brain dynamics.

Human brain mapping
Large-scale brain dynamics are believed to lie in a latent, low-dimensional space. Typically, the embeddings of brain scans are derived independently from different cognitive tasks or resting-state data, ignoring a potentially large-and shared-portio...

Assessing the utility of deep neural networks in predicting postoperative surgical complications: a retrospective study.

The Lancet. Digital health
BACKGROUND: Early detection of postoperative complications, including organ failure, is pivotal in the initiation of targeted treatment strategies aimed at attenuating organ damage. In an era of increasing health-care costs and limited financial reso...

State-of-the-art machine learning algorithms for the prediction of outcomes after contemporary heart transplantation: Results from the UNOS database.

Clinical transplantation
PURPOSE: We sought to develop and validate machine learning (ML) models to increase the predictive accuracy of mortality after heart transplantation (HT).

Quantitative Analysis and Automated Lung Ultrasound Scoring for Evaluating COVID-19 Pneumonia With Neural Networks.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
As being radiation-free, portable, and capable of repetitive use, ultrasonography is playing an important role in diagnosing and evaluating the COVID-19 Pneumonia (PN) in this epidemic. By virtue of lung ultrasound scores (LUSS), lung ultrasound (LUS...

Reproducibility of automated habenula segmentation via deep learning in major depressive disorder and normal controls with 7 Tesla MRI.

Scientific reports
The habenula is one of the most important brain regions for investigating the etiology of psychiatric diseases such as major depressive disorder (MDD). However, the habenula is challenging to delineate with the naked human eye in brain imaging due to...

Machine Learning for Predicting the 3-Year Risk of Incident Diabetes in Chinese Adults.

Frontiers in public health
We aimed to establish and validate a risk assessment system that combines demographic and clinical variables to predict the 3-year risk of incident diabetes in Chinese adults. A 3-year cohort study was performed on 15,928 Chinese adults without dia...