Geriatrics

Fault Recognition Method Based on Attention Mechanism and the 3D-UNet.

Oil and gas reservoirs are of great significance for economic benefits. Faults act as important conduits for transporting hydrocarbons and as essential sealing conditions. The location and morphology of faults reflect changes in the shape of the strata, so fault interpretation of seismic data has been an essential task in oil and gas exploration and development. The traditional fault identificatio...

Machine Learning for Healthcare Wearable Devices: The Big Picture.

Using artificial intelligence and machine learning techniques in healthcare applications has been actively researched over the last few years. It holds promising opportunities as it is used to track human activities and vital signs using wearable devices and assist in diseases' diagnosis, and it can play a great role in elderly care and patient's health monitoring and diagnostics. With the great t...

A Novel Approach of Feature Space Reconstruction with Three-Way Decisions for Long-Tailed Text Classification.

Text classification is widely studied by researchers in the natural language processing field. However, real-world text data often follow a long-taile...

A Tightly Coupled LiDAR-Inertial SLAM for Perceptually Degraded Scenes.

Realizing robust six degrees of freedom (6DOF) state estimation and high-performance simultaneous localization and mapping (SLAM) for perceptually deg...

Predicting Brain Age Using Machine Learning Algorithms: A Comprehensive Evaluation.

Machine learning (ML) algorithms play a vital role in the brain age estimation frameworks. The impact of regression algorithms on prediction accuracy ...

Deep learning -- promises for 3D nuclear imaging: a guide for biologists.

For the past century, the nucleus has been the focus of extensive investigations in cell biology. However, many questions remain about how its shape a...

End-to-End Lip-Reading Open Cloud-Based Speech Architecture.

Deep learning technology has encouraged research on noise-robust automatic speech recognition (ASR). The combination of cloud computing technologies a...

Prediction of femoral strength of elderly men based on quantitative computed tomography images using machine learning.

Hip fracture is the most common complication of osteoporosis, and its major contributor is compromised femoral strength. This study aimed to develop p...

Assessment of the predictive potential of cognitive scores from retinal images and retinal fundus metadata via deep learning using the CLSA database.

Accumulation of beta-amyloid in the brain and cognitive decline are considered hallmarks of Alzheimer's disease. Knowing from previous studies that th...

The impact of transfer learning on 3D deep learning convolutional neural network segmentation of the hippocampus in mild cognitive impairment and Alzheimer disease subjects.

Research on segmentation of the hippocampus in magnetic resonance images through deep learning convolutional neural networks (CNNs) shows promising re...

Multigraph classification using learnable integration network with application to gender fingerprinting.

Multigraphs with heterogeneous views present one of the most challenging obstacles to classification tasks due to their complexity. Several works base...

A Survey of End-to-End Driving: Architectures and Training Methods.

Autonomous driving is of great interest to industry and academia alike. The use of machine learning approaches for autonomous driving has long been st...

CIPHER-SC: Disease-Gene Association Inference Using Graph Convolution on a Context-Aware Network With Single-Cell Data.

Inference of disease-gene associations helps unravel the pathogenesis of diseases and contributes to the treatment. Although many machine learning-bas...

Deep learning for automatic segmentation of paraspinal muscle on computed tomography.

BACKGROUND: Muscle quantification is an essential step in sarcopenia evaluation.

Effect of dataset size, image quality, and image type on deep learning-based automatic prostate segmentation in 3D ultrasound.

Three-dimensional (3D) transrectal ultrasound (TRUS) is utilized in prostate cancer diagnosis and treatment, necessitating time-consuming manual prost...

Hallmarks of aging-based dual-purpose disease and age-associated targets predicted using PandaOmics AI-powered discovery engine.

Aging biology is a promising and burgeoning research area that can yield dual-purpose pathways and protein targets that may impact multiple diseases, ...

A deep learning MRI approach outperforms other biomarkers of prodromal Alzheimer's disease.

BACKGROUND: The three core pathologies of Alzheimer's disease (AD) are amyloid pathology, tau pathology, and neurodegeneration. Biomarkers exist for e...

Research on Data Analysis Network of TCM Tongue Diagnosis Based on Deep Learning Technology.

The aim of the study is to build a tongue image intelligent analysis "end-to-end" deep learning network based on a tongue diagnosis image of tradition...

Effect Evaluation of Electronic Health PDCA Nursing in Treatment of Childhood Asthma with Artificial Intelligence.

Asthma in children has a long duration and is prone to recurring attacks. Children will feel chest tightness, shortness of breath, cough, and difficul...

Deep Learning Classification of Spinal Osteoporotic Compression Fractures on Radiographs using an Adaptation of the Genant Semiquantitative Criteria.

RATIONALE AND OBJECTIVES: Osteoporosis affects 9% of individuals over 50 in the United States and 200 million women globally. Spinal osteoporotic comp...