AIMC Topic: Young Adult

Clear Filters Showing 1661 to 1670 of 5268 articles

State-of-the-art sleep arousal detection evaluated on a comprehensive clinical dataset.

Scientific reports
Aiming to apply automatic arousal detection to support sleep laboratories, we evaluated an optimized, state-of-the-art approach using data from daily work in our university hospital sleep laboratory. Therefore, a machine learning algorithm was traine...

The neural network RTNet exhibits the signatures of human perceptual decision-making.

Nature human behaviour
Convolutional neural networks show promise as models of biological vision. However, their decision behaviour, including the facts that they are deterministic and use equal numbers of computations for easy and difficult stimuli, differs markedly from ...

Medical intelligence using PPG signals and hybrid learning at the edge to detect fatigue in physical activities.

Scientific reports
The educational environment plays a vital role in the development of students who participate in athletic pursuits both in terms of their physical health and their ability to detect fatigue. As a result of recent advancements in deep learning and bio...

The clinical value of artificial intelligence in assisting junior radiologists in thyroid ultrasound: a multicenter prospective study from real clinical practice.

BMC medicine
BACKGROUND: This study is to propose a clinically applicable 2-echelon (2e) diagnostic criteria for the analysis of thyroid nodules such that low-risk nodules are screened off while only suspicious or indeterminate ones are further examined by histop...

Deep learning classification performance for diagnosing condylar osteoarthritis in patients with dentofacial deformities using panoramic temporomandibular joint projection images.

Oral radiology
OBJECTIVE: The present study aimed to assess the consistencies and performances of deep learning (DL) models in the diagnosis of condylar osteoarthritis (OA) among patients with dentofacial deformities using panoramic temporomandibular joint (TMJ) pr...

Explainable deep learning and biomechanical modeling for TMJ disorder morphological risk factors.

JCI insight
Clarifying multifactorial musculoskeletal disorder etiologies supports risk analysis, development of targeted prevention, and treatment modalities. Deep learning enables comprehensive risk factor identification through systematic analyses of disease ...

Multi-Modal Electrophysiological Source Imaging With Attention Neural Networks Based on Deep Fusion of EEG and MEG.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The process of reconstructing underlying cortical and subcortical electrical activities from Electroencephalography (EEG) or Magnetoencephalography (MEG) recordings is called Electrophysiological Source Imaging (ESI). Given the complementarity betwee...

Cross-cultural comparison of beauty judgments in visual art using machine learning analysis of art attribute predictors among Japanese and German speakers.

Scientific reports
In empirical art research, understanding how viewers judge visual artworks as beautiful is often explored through the study of attributes-specific inherent characteristics or artwork features such as color, complexity, and emotional expressiveness. T...

Enhanced Muscle Activation Using Robotic Assistance Within the Electromechanical Delay: Implications for Rehabilitation?

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Robotic rehabilitation has been shown to match the effects of conventional physical therapy on motor function for patients with neurological diseases. Rehabilitation robots have the potential to reduce therapists' workload in time-intensive training ...