AIMC Topic:
Young Adult

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Inter-individual deep image reconstruction via hierarchical neural code conversion.

NeuroImage
The sensory cortex is characterized by general organizational principles such as topography and hierarchy. However, measured brain activity given identical input exhibits substantially different patterns across individuals. Although anatomical and fu...

Deep convolutional neural network-the evaluation of cervical vertebrae maturation.

Oral radiology
OBJECTIVES: This study aimed to automatically determine the cervical vertebral maturation (CVM) processes on lateral cephalometric radiograph images using a proposed deep learning-based convolutional neural network (CNN) model and to test the success...

The effect of robot-assisted walking in different modalities on cardiorespiratory responses and energy consumption in patients with subacute stroke.

Neurological research
OBJECTIVES: The aim of our study was to evaluate the effect of robot-assisted walking in different modalities on cardiorespiratory responses and energy consumption in subacute stroke patients.

A Novel Mini-Invasive Technique of Arthroscopic-Assisted Reduction and Robot-Assisted Fixation for Trans-Scaphoid Perilunate Fracture Dislocations.

Orthopaedic surgery
OBJECTIVE: Perilunate injuries are rare but devastating carpal injuries. The treatment of perilunate injuries remains challenging and contentious. This study aims to describe a novel mini-invasive surgical technique of arthroscopic-assisted reduction...

The use of deep learning for smartphone-based human activity recognition.

Frontiers in public health
The emerging field of digital phenotyping leverages the numerous sensors embedded in a smartphone to better understand its user's current psychological state and behavior, enabling improved health support systems for patients. As part of this work, a...

Application of Artificial Intelligence to Quantitative Assessment of Fundus Tessellated Density in Young Adults with Different Refractions.

Ophthalmic research
INTRODUCTION: The aim of this study was to quantitatively assess fundus tessellated density (FTD) and associated factors by artificial intelligence (AI) in young adults.

Evaluation of a deep learning-based reconstruction method for denoising and image enhancement of shoulder MRI in patients with shoulder pain.

European radiology
OBJECTIVES: To evaluate the diagnostic performance of an automated reconstruction algorithm combining MR imaging acquired using compressed SENSE (CS) with deep learning (DL) in order to reconstruct denoised high-quality images from undersampled MR im...

A population-based study to assess two convolutional neural networks for dental age estimation.

BMC oral health
BACKGROUND: Dental age (DA) estimation using two convolutional neural networks (CNNs), VGG16 and ResNet101, remains unexplored. In this study, we aimed to investigate the possibility of using artificial intelligence-based methods in an eastern Chines...

Deep learning in sex estimation from a peripheral quantitative computed tomography scan of the fourth lumbar vertebra-a proof-of-concept study.

Forensic science, medicine, and pathology
Sex estimation is a key element in the analysis of unknown skeletal remains. The vertebrae display clear sex discrepancy and have proven accurate in conventional morphometric sex estimation. This proof-of-concept study aimed to investigate the possib...