Geriatrics

Characteristic analysis and fuzzy simulation of falls-from-height mechanics, and case studies.

In this paper, methods for scientifically inferring the causes of the falls-from-height accidents, that is, the initial fall postures, and reconstructing the fall accident are presented. For this purpose, the general types of fall were subdivided into eight, and the characteristics of each fall type were analyzed. An initial posture estimation tool based on Fuzzy method was developed utilizing the...

End-to-End Deep Learning Fusion of Fingerprint and Electrocardiogram Signals for Presentation Attack Detection.

Although fingerprint-based systems are the commonly used biometric systems, they suffer from a critical vulnerability to a presentation attack (PA). Therefore, several approaches based on a fingerprint biometrics have been developed to increase the robustness against a PA. We propose an alternative approach based on the combination of fingerprint and electrocardiogram (ECG) signals. An ECG signal ...

Biohorology and biomarkers of aging: Current state-of-the-art, challenges and opportunities.

The aging process results in multiple traceable footprints, which can be quantified and used to estimate an organism's age. Examples of such aging bio...

Application of Generalized Split Linearized Bregman Iteration algorithm for Alzheimer's disease prediction.

In this paper, we applied a novel method for the detection of Alzheimer's disease (AD) based on a structural magnetic resonance imaging (sMRI) dataset...

Network topology and machine learning analyses reveal microstructural white matter changes underlying Chinese medicine Dengzhan Shengmai treatment on patients with vascular cognitive impairment.

With the increasing incidence of cerebrovascular diseases and dementia, considerable efforts have been made to develop effective treatments on vascula...

Scalable diagnostic screening of mild cognitive impairment using AI dialogue agent.

The search for early biomarkers of mild cognitive impairment (MCI) has been central to the Alzheimer's Disease (AD) and dementia research community in...

Grid-Based Mobile Robot Path Planning Using Aging-Based Ant Colony Optimization Algorithm in Static and Dynamic Environments.

Planning an optimal path for a mobile robot is a complicated problem as it allows the mobile robots to navigate autonomously by following the safest a...

Identification of Methylated Gene Biomarkers in Patients with Alzheimer's Disease Based on Machine Learning.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder and characterized by the cognitive impairments. It is essential to identify poten...

Human activity recognition using magnetic induction-based motion signals and deep recurrent neural networks.

Recognizing human physical activities using wireless sensor networks has attracted significant research interest due to its broad range of application...

Alzheimer's disease, mild cognitive impairment, and normal aging distinguished by multi-modal parcellation and machine learning.

A 360-area surface-based cortical parcellation is extended to study mild cognitive impairment (MCI) and Alzheimer's disease (AD) from healthy control ...

Machine Learning Analysis of Digital Clock Drawing Test Performance for Differential Classification of Mild Cognitive Impairment Subtypes Versus Alzheimer's Disease.

OBJECTIVE: To determine how well machine learning algorithms can classify mild cognitive impairment (MCI) subtypes and Alzheimer's disease (AD) using ...

Review of Stereo Matching Algorithms Based on Deep Learning.

Stereo vision is a flourishing field, attracting the attention of many researchers. Recently, leveraging on the development of deep learning, stereo m...

Human vs. machine: the psychological and behavioral consequences of being compared to an outperforming artificial agent.

While artificial agents (AA) such as Artificial Intelligence are being extensively developed, a popular belief that AA will someday surpass human inte...

Multi-modular AI Approach to Streamline Autism Diagnosis in Young Children.

Autism has become a pressing healthcare challenge. The instruments used to aid diagnosis are time and labor expensive and require trained clinicians t...

DeeplyTough: Learning Structural Comparison of Protein Binding Sites.

Protein pocket matching, or binding site comparison, is of importance in drug discovery. Identification of similar binding pockets can help guide effo...

Identifying Lung Cancer Risk Factors in the Elderly Using Deep Neural Networks: Quantitative Analysis of Web-Based Survey Data.

BACKGROUND: Lung cancer is one of the most dangerous malignant tumors, with the fastest-growing morbidity and mortality, especially in the elderly. Wi...

Value of a Machine Learning Approach for Predicting Clinical Outcomes in Young Patients With Hypertension.

Risk stratification of young patients with hypertension remains challenging. Generally, machine learning (ML) is considered a promising alternative to...

Deep-learning- and pharmacophore-based prediction of RAGE inhibitors.

The receptor for advanced glycation end products (RAGE) has been identified as a therapeutic target in a host of pathological diseases, including Alzh...

Postanesthesia care unit delirium following robot-assisted vs open retropubic radical prostatectomy: A prospective observational study.

BACKGROUND: The aim of this study was to compare the incidence of early postoperative delirium in the postanesthesia care unit (PACU) between robot-as...

BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets.

Understanding how cognitive functions emerge from brain structure depends on quantifying how discrete regions are integrated within the broader cortic...