Geriatrics

Layer-Specific Colocalization of Microglia with Amyloid Plaques in the Middle Temporal Gyrus Predicts Cognitive Decline in Alzheimer's Disease.

Alzheimer's disease (AD), the most common form of dementia, is marked by cognitive decline and amyloid-beta (Aβ) plaque deposition in the brain. Microglia cluster around Aβ plaques shifting to a plaque-associated microglia (PAM) immunophenotype. This study investigates the association between Aβ, microglia and PAM with cognitive performance in 75 older adults, 39 with normal cognition and 36 with ...

A Comparison of Machine Learning-Based Models and a Simple Clinical Bedside Tool to Predict Morbidity and Mortality After Gastrointestinal Cancer Surgery in the Elderly.

Frailty in the elderly population is associated with increased vulnerability to stressors, including surgical interventions. This study compared machine learning (ML) models with a clinical bedside tool, the Gastrointestinal Surgery Frailty Index (GiS-FI), for predicting mortality and morbidity in elderly patients undergoing gastrointestinal cancer surgery. In a multicenter analysis of 937 patient...

Alzheimer's diagnosis by an efficient pipelined gene selection model based on statistical and biological data analysis.

Diagnosing Alzheimer's disease based on gene expression data extracted from microarrays is still an open field of research. Due to the availability of...

Investigating Elderly Individuals' Acceptance of Artificial Intelligence (AI)-Powered Companion Robots: The Influence of Individual Characteristics.

The emergence of AI companion robots is transforming the landscape of elderly care, offering numerous conveniences to senior citizens when their child...

Reimagining Resilience in Aging: Leveraging AI/ML, Big Data Analytics, and Systems Innovation.

As the aging population in the United States grows, the need for an integrated approach to support older adults has become increasingly urgent. The SU...

Brain metabolic imaging-based model identifies cognitive stability in prodromal Alzheimer's disease.

The recent approval of anti-amyloid pharmaceuticals for the treatment of Alzheimer's disease (AD) has created a pressing need for the ability to accur...

Impact of sarcopenia and obesity on mortality in older adults with SARS-CoV-2 infection: automated deep learning body composition analysis in the NAPKON-SUEP cohort.

INTRODUCTION: Severe respiratory infections pose a major challenge in clinical practice, especially in older adults. Body composition analysis could p...

SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices.

The proliferation of end devices has led to a distributed computing paradigm, wherein on-device machine learning models continuously process diverse d...

Screen shooting resistant watermarking based on cross attention.

With the development of digital imaging devices, the process of recording sensitive information displayed on screens through mobile phones and cameras...

Dynamic Predictive Models of Cardiogenic Shock in STEMI: Focus on Interventional and Critical Care Phases.

: While early risk stratification in STEMI is essential, the threat of cardiogenic shock (CS) persists after revascularization due to reperfusion inju...

High-Resolution Spatial Profiling of Microglia Reveals Proximity Associated Immunometabolic Reprogramming in Alzheimer's Disease.

Single-cell RNA sequencing has demonstrated that the presence of parenchymal amyloid plaques and intracellular hyperphosphorylated tau pathology is as...

Assessing perioperative risks in a mixed elderly surgical population using machine learning: A multi-objective symbolic regression approach to cardiorespiratory fitness derived from cardiopulmonary exercise testing.

Accurate preoperative risk assessment is of great value to both patients and clinical teams. Several risk scores have been developed but are often not...

Expected length of stay in residential aged care facilities in Australia: Assessing the impact of dementia using machine learning.

Interpretable machine learning for precision cognitive aging.

INTRODUCTION: Machine performance has surpassed human capabilities in various tasks, yet the opacity of complex models limits their adoption in critic...

A Large Language Model Approach to Identifying Preoperative Frailty Among Older Adults From Clinical Notes.

BACKGROUND: Patients with frailty have a higher risk of major postoperative mortality and morbidity. Identifying frailty from the medical record, howe...

Predicting Immunotherapy Response in Unresectable Hepatocellular Carcinoma: A Comparative Study of Large Language Models and Human Experts.

Hepatocellular carcinoma (HCC) is an aggressive cancer with limited biomarkers for predicting immunotherapy response. Recent advancements in large lan...

Early detection of Alzheimer's disease progression stages using hybrid of CNN and transformer encoder models.

Alzheimer's disease (AD) is a neurodegenerative disorder that affects memory and cognitive functions. Manual diagnosis is prone to human error, often ...

Biodentine Counteracts the Aging Process of Human Dental Pulp Stem Cells Through Wnt/β-Catenin Pathway.

OBJECTIVES: This study aimed to evaluate the effects of Biodentine on human Dental Pulp Stem Cells (hDPSCs) proliferation and senescence and explore t...

Exosomes derived from human umbilical cord mesenchymal stem cells attenuate senescence of peritoneal mesothelial cells by inhibiting oxidative stress.

OBJECTIVE: Aging is a natural process that affects cellular function. In peritoneal dialysis (PD), chronic exposure to dialysate induces oxidative str...

The two cut-offs approach for plasma p-tau217 in detecting Alzheimer's disease in subjective cognitive decline and mild cognitive impairment.

BACKGROUND: The study aimed to explore the applicability of plasma phosphorylated tau (p-tau)217 in identifying patients with subjective cognitive dec...