Geriatrics

Fuzzy-Rough Cognitive Networks: Theoretical Analysis and Simpler Models.

Fuzzy-rough cognitive networks (FRCNs) are recurrent neural networks (RNNs) intended for structured ...

End-to-end deep learning for interior tomography with low-dose x-ray CT.

There are several x-ray computed tomography (CT) scanning strategies used to reduce radiation dose, ...

Confusion regarding the use of Natural Language Processing in ICU delirium assessment.

Natural language processing and detecting delirium.

MultiHeadGAN: A deep learning method for low contrast retinal pigment epithelium cell segmentation with fluorescent flatmount microscopy images.

BACKGROUND: Retinal pigment epithelium (RPE) aging is an important cause of vision loss. As RPE agin...

End-to-End Sentence-Level Multi-View Lipreading Architecture with Spatial Attention Module Integrated Multiple CNNs and Cascaded Local Self-Attention-CTC.

Concomitant with the recent advances in deep learning, automatic speech recognition and visual speec...

Deep learning-based brain age prediction in normal aging and dementia.

Brain aging is accompanied by patterns of functional and structural change. Alzheimer's disease (AD)...

Smart Memory Storage Solution and Elderly Oriented Smart Equipment Design under Deep Learning.

This study explores the memory characteristics of elderly individuals to design effective smart devi...

Machine learning model prediction of 6-month functional outcome in elderly patients with intracerebral hemorrhage.

Spontaneous intracerebral hemorrhage (ICH) has an increasing incidence and a worse outcome in elderl...

Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology.

Artificial intelligence (AI) can extract visual information from histopathological slides and yield ...

Deep-Learning-Assisted Stratification of Amyloid Beta Mutants Using Drying Droplet Patterns.

The development of simple and accurate methods to predict mutations in proteins remains an unsolved ...

Identifying Blood Biomarkers for Dementia Using Machine Learning Methods in the Framingham Heart Study.

Blood biomarkers for dementia have the potential to identify preclinical disease and improve partici...

Cardiac auscultation predicts mortality in elderly patients admitted for COVID-19.

INTRODUCTION: COVID-19 has had a great impact on the elderly population. All admitted patients under...

Therapeutic use of the humanoid robot, Telenoid, with older adults: A critical interpretive synthesis review.

This review sought to critically evaluate the use of the teleoperated humanoid robotic communication...

Dietary administration of D-chiro-inositol attenuates sex-specific metabolic imbalances in the 5xFAD mouse model of Alzheimer's disease.

Increasing evidence shows that hypothalamic dysfunction, insulin resistance, and weight loss precede...

Dementia risk predictions from German claims data using methods of machine learning.

INTRODUCTION: We examined whether German claims data are suitable for dementia risk prediction, how ...

Histopathology-Based Diagnosis of Oral Squamous Cell Carcinoma Using Deep Learning.

Oral squamous cell carcinoma (OSCC) is prevalent around the world and is associated with poor progno...

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 cond...

Machine Learning for Healthcare Wearable Devices: The Big Picture.

Using artificial intelligence and machine learning techniques in healthcare applications has been ac...

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. Howev...

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

Realizing robust six degrees of freedom (6DOF) state estimation and high-performance simultaneous lo...