Geriatrics

MDSFD-Net: Alzheimer's disease diagnosis with missing modality via disentanglement learning and feature distillation.

Multi-modal analysis can provide complementary information and significantly aid in the early diagnosis and intervention of Alzheimer's Disease (AD). However, the issue of missing modalities presents a major challenge, as most methods that rely on complete multi-modal data become infeasible. The most advanced approaches to addressing missing modalities typically use generative models, but these of...

Muscle Composition as a Novel Prognostic Tool for Pain, Frailty, and Sarcopenia.

A clinical observation common to both sarcopenia and frailty is compositional changes to skeletal muscles. Automatic segmentation and quantification of skeletal muscle composition using imaging modalities such as computed tomography or MRI have indicated compositional changes are a sensitive biomarker for various diseases and disorders. This article examines the integration of clinical investigati...

Metacognition for Unknown Situations and Environments (MUSE).

Metacognition, defined as the awareness and regulation of one's cognitive processes, is central to human adaptability in unknown situations. In contra...

Artificial Intelligence, Informatics, and Pain in Aging.

The aging population is disproportionately affected by pain in the acute care setting. Due to the complexity of the pain experience, pain management p...

Nurses' Perspectives on AI in Clinical Practice: Implications for Training and Workforce Development.

This study explored nurses' perspectives on the adoption and utilization of artificial intelligence (AI) in clinical practice within a large universit...

Decision Strategies in AI-Based Ensemble Models in Opportunistic Alzheimer's Detection from Structural MRI.

Alzheimer's disease (AD) is a neurodegenerative condition and the most common form of dementia. Recent developments in AD treatment call for robust di...

Single Port Robot-Assisted Supraclavicular Flap Repair of Iatrogenic Hardware-Associated Pharyngeal Perforation: A Case Report.

BACKGROUND: The incidence of iatrogenic pharyngeal perforation has been reported to comprise 50%-75% of all pharyngeal perforations. In the context of...

ToBaFu: Topology-based fusion model for classification of two-dimensional cancer images.

Medical images play a pivotal role in disease diagnosis. Numerous studies on cancer image analysis focus on end-to-end deep neural networks, neglectin...

EKDSC: Long-tailed recognition based on expert knowledge distillation for specific categories.

In the field of long-tail visual recognition, the imbalance in data distribution leads to a significant performance gap between head and tail classes....

Attention Gated-VGG with deep learning-based features for Alzheimer's disease classification.

BACKGROUND: Alzheimer's disease (AD) is considered to be one of the neurodegenerative diseases with possible cognitive deficits related to dementia in...

Multi-modal orthogonal fusion network via cross-layer guidance for Alzheimer's disease diagnosis.

Multi-modal neuroimaging techniques are widely employed for the accurate diagnosis of Alzheimer's Disease (AD). Existing fusion methods typically focu...

Prostate MR image segmentation using a multi-stage network approach.

Prostate cancer (PCa) remains one of the most prevalent cancers among men, with over 1.4 million new cases and 375,304 deaths reported globally in 202...

Development and Validation of a Machine Learning-Based Risk Prediction Model for Delirium in Older Inpatients: A Prospective Cohort Study.

AIMS: To develop and validate a machine learning-based risk prediction model for delirium in older inpatients. DESIGN: A prospective cohort study. MET...

AlzhiNet: Traversing from 2D-CNN to 3D-CNN, Towards Early Detection and Diagnosis of Alzheimer's Disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder with increasing prevalence among the ageing population, necessitating early and a...

Proteomic signature of dementia risk in type 2 diabetes.

INTRODUCTION: Type 2 diabetes (T2D) significantly increases dementia risk, yet the molecular mechanisms underlying this association remain unclear. OB...

Detection of aging-induced vascular remodeling based on Raman imaging and deep learning.

Vascular aging-related remodeling is a common pathological basis for many chronic diseases, so early detection of physical arterial aging is important...

Six promising drug repurposing candidates for Alzheimer's disease and their sex-specific mechanisms and efficacy.

Alzheimer's disease is a neurodegenerative disorder that leads to progressive memory loss, cognitive decline, and behavioral changes. Despite ongoing ...

Machine Learning-Driven Radiomic Profiling of Thalamus-Amygdala Nuclei for Prediction of Postoperative Delirium After STN-DBS in Parkinson's Disease Patients: A Pilot Study.

Postoperative delirium is a common complication following sub-thalamic nucleus deep brain stimulation surgery in Parkinson's disease patients. Postope...

Longitudinal Validation of the Artificial Intelligence Algorithm in Home OCT for Age-Related Macular Degeneration-Report 3.

PURPOSE: Longitudinal validation of the artificial intelligence-based Notal OCT Analyzer (NOA) for identification of clinically significant changes in...

Integrating Time and Frequency Domain Features of fMRI Time Series for Alzheimer's Disease Classification Using Graph Neural Networks.

Accurate and early diagnosis of Alzheimer's Disease (AD) is crucial for timely interventions and treatment advancement. Functional Magnetic Resonance ...