AIMC Topic: Humans

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Forecasting hand-foot-and-mouth disease cases using wavelet-based SARIMA-NNAR hybrid model.

PloS one
BACKGROUND: Hand-foot-and-mouth disease_(HFMD) is one of the most typical diseases in children that is associated with high morbidity. Reliable forecasting is crucial for prevention and control. Recently, hybrid models have become popular, and wavele...

CapsField: Light Field-Based Face and Expression Recognition in the Wild Using Capsule Routing.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Light field (LF) cameras provide rich spatio-angular visual representations by sensing the visual scene from multiple perspectives and have recently emerged as a promising technology to boost the performance of human-machine systems such as biometric...

Multitask Non-Autoregressive Model for Human Motion Prediction.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Human motion prediction, which aims at predicting future human skeletons given the past ones, is a typical sequence-to-sequence problem. Therefore, extensive efforts have been devoted to exploring different RNN-based encoder-decoder architectures. Ho...

Robotic lower extremity exoskeleton use in a non-ambulatory child with cerebral palsy: a case study.

Disability and rehabilitation. Assistive technology
PURPOSE: With few treatment options available for non-ambulatory children with cerebral palsy (CP), a robotic lower extremity gait trainer may provide a non-invasive addition to conventional treatment options. This case study investigates the usage a...

Development of a deep-learning system for detection of lattice degeneration, retinal breaks, and retinal detachment in tessellated eyes using ultra-wide-field fundus images: a pilot study.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To investigate the detection of lattice degeneration, retinal breaks, and retinal detachment in tessellated eyes using ultra-wide-field fundus imaging system (Optos) with convolutional neural network technology.

Machine learning algorithms to predict seizure due to acute tramadol poisoning.

Human & experimental toxicology
INTRODUCTION: This study was designed to develop and evaluate machine learning algorithms for predicting seizure due to acute tramadol poisoning, identifying high-risk patients and facilitating appropriate clinical decision-making.

Global guidance network for breast lesion segmentation in ultrasound images.

Medical image analysis
Automatic breast lesion segmentation in ultrasound helps to diagnose breast cancer, which is one of the dreadful diseases that affect women globally. Segmenting breast regions accurately from ultrasound image is a challenging task due to the inherent...

Neural network enhanced 3D turbo spin echo for MR intracranial vessel wall imaging.

Magnetic resonance imaging
PURPOSE: To improve the signal-to-noise ratio (SNR) and image sharpness for whole brain isotropic 0.5 mm three-dimensional (3D) T weighted (Tw) turbo spin echo (TSE) intracranial vessel wall imaging (IVWI) at 3 T.

Pattern classification as decision support tool in antipsychotic treatment algorithms.

Experimental neurology
Pattern classification aims to establish a new approach in personalized treatment. The scope is to tailor treatment on individual characteristics during all phases of care including prevention, diagnosis, treatment, and clinical outcome. In psychotic...