Geriatrics

Healthcare Big Data in Hong Kong: Development and Implementation of Artificial Intelligence-Enhanced Predictive Models for Risk Stratification.

Routinely collected electronic health records (EHRs) data contain a vast amount of valuable informat...

Use of Artificial Intelligence in the Identification and Diagnosis of Frailty Syndrome in Older Adults: Scoping Review.

BACKGROUND: Frailty syndrome (FS) is one of the most common noncommunicable diseases, which is assoc...

Using natural language processing to increase prediction and reduce subgroup differences in personnel selection decisions.

The purpose of this research is to demonstrate how using natural language processing (NLP) on narrat...

A Concentric Tube Steerable Drilling Robot for Minimally Invasive Spinal Fixation of Osteoporotic Vertebrae.

Spinal fixation with rigid pedicle screws have shown to be an effective treatment for many patients....

Liquid-biopsy proteomics combined with AI identifies cellular drivers of eye aging and disease in vivo.

Single-cell analysis in living humans is essential for understanding disease mechanisms, but it is i...

Using an adaptive network-based fuzzy inference system for prediction of successful aging: a comparison with common machine learning algorithms.

INTRODUCTION: The global society is currently facing a rise in the elderly population. The concept o...

Temperature and haemodynamic effects of a 100 mL bolus of 20% albumin at room versus body temperature in cardiac surgery patients.

To study the temperature and haemodynamic effects of room versus body temperature 20% albumin fluid...

Deep learning based diagnosis of Alzheimer's disease using FDG-PET images.

PURPOSE: The aim of this study is to develop a deep neural network to diagnosis Alzheimer's disease ...

Research on a New Rehabilitation Robot for Balance Disorders.

The treatment of patients with balance disorders is an urgent problem to be solved by the medical co...

Class-Balanced Deep Learning with Adaptive Vector Scaling Loss for Dementia Stage Detection.

Alzheimer's disease (AD) leads to irreversible cognitive decline, with Mild Cognitive Impairment (MC...

Automatic selection of spoken language biomarkers for dementia detection.

This paper analyzes diverse features extracted from spoken language to select the most discriminativ...

Artificial intelligence for dementia prevention.

INTRODUCTION: A wide range of modifiable risk factors for dementia have been identified. Considerabl...

c-Diadem: a constrained dual-input deep learning model to identify novel biomarkers in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is an incurable, debilitating neurodegenerative disorder. Curre...

A 48-Year-Old Man With a Hip Fracture and Skin Rash: A Case Report.

BACKGROUND/OBJECTIVE: Patients with systemic mastocytosis are at high risk of developing osteoporosi...

Speech and language processing with deep learning for dementia diagnosis: A systematic review.

Dementia is a progressive neurodegenerative disease that burdens the person living with the disease,...

Attenuative effects of collagen peptide from milkfish () scales on ovariectomy-induced osteoporosis.

Osteoporosis is characterized by low bone mass, bone microarchitecture disruption, and collagen loss...

Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data.

BACKGROUND: Deep learning has shown potential in various scientific domains but faces challenges whe...

Cyberethics in nursing education: Ethical implications of artificial intelligence.

As the use of artificial intelligence (AI) technologies, particularly generative AI (Gen AI), become...

Chart Review Is Dead; Long Live Chart Review: How Artificial Intelligence Will Make Human Review of Medical Records Obsolete, One Day.

Spectral analysis and Bi-LSTM deep network-based approach in detection of mild cognitive impairment from electroencephalography signals.

Mild cognitive impairment (MCI) is a neuropsychological syndrome that is characterized by cognitive ...

E2EDA: Protein Domain Assembly Based on End-to-End Deep Learning.

With the development of deep learning, almost all single-domain proteins can be predicted at experim...