Geriatrics

Herbal extracts as antibiotic adjuvants against ESKAPE pathogens: mechanisms and therapeutic potential.

The escalating crisis of antimicrobial resistance, particularly driven by ESKAPE pathogens, poses a serious threat to global public health. With the stagnant pipeline of novel antibiotic discovery, repurposing herbal extracts as antibiotic adjuvants to revive existing therapies is a promising strategy. This review systematically elaborates the multi-faceted mechanisms by which herbal extracts and ...

Association of MRI-Visible Perivascular Spaces With Longitudinal Cognitive Decline Over a Decade.

BACKGROUND AND OBJECTIVES: Cerebral small vessel disease (SVD) is the most common vascular contributor to dementia. SVD markers often coexist, contributing to difficulty assessing their independent contributions to cognitive domains. MRI-visible perivascular spaces (PVSs) are an emerging SVD marker visualized by MRI. We previously showed that basal ganglia PVSs cross-sectionally contribute to wors...

Polypharmacy, Medicine Optimisation, and Medication Adherence in Older Cancer Patients.

Olfactory radiomics signatures link pTau217 to cognitive impairment in probable Alzheimer's disease: a multi-cohort machine learning study.

Predicting multiple sclerosis from radiologically isolated syndrome using generative artificial intelligence.

Radiologically Isolated Syndrome (RIS) is characterized by incidental MRI findings indicative of multiple sclerosis (MS) in asymptomatic individuals. ...

Association of the neutrophil percentage-to-albumin ratio with sarcopenia in U.S. adults: Evidence from NHANES 2011-2018 and machine learning-based analyses.

BACKGROUND: Sarcopenia is an age-related muscle disorder driven by complex interactions between chronic inflammation and nutritional imbalance. The ne...

Large Language Models for Cardiac MRI Diagnosis Based on Standardized Text Descriptions.

BACKGROUND: MRI is important for cardiac disease evaluation, but accurate diagnosis remains challenging in less experienced centers. Although large la...

[Participatory processes in the development of AI systems in a clinical context: A qualitative secondary analysis].

Participatory processes in the development of AI systems in a clinical context: A qualitative secondary analysis Abstract: Background: Despite technol...

Leveraging routine clinical data for dementia risk prediction using machine learning.

BackgroundEarly diagnosis of dementia is essential for enabling timely interventions that may slow disease progression, improve patient outcomes, and ...

Explainable Machine Learning and Deep Learning Models for Understanding Operational and Degradation Effects in Nafion Membranes.

Understanding how chemical degradation influences proton transport in Nafion membranes is critical for improving the reliability of proton exchange me...

Decoupling MCI-specific signatures from shared neurobiological substrates of cognitive aging via deep learning.

The specific neuroanatomy of mild cognitive impairment (MCI) is obscured by its clinical heterogeneity and confounding effects from normative variatio...

Robust validation of neuroimaging and clinical models via the SAR method: A case study based on the ADNI dataset.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and substantial brain atrophy. Early and accur...

Dysfunction of the neurovascular unit as a temporal driver in Alzheimer's pathogenesis.

Extensive studies have shown that cerebrovascular dysfunction is a critical factor in the onset and progression of Alzheimer's disease (AD). Neurovasc...

Wearable Cardiac Devices as Windows Into Physiological Decline: A Review of Digital Biomarkers in the Prevention, Detection, and Management of Cardiogeriatric Frailty.

In patients with cardiovascular disease (CVD), frailty is a significant problem due to its association with morbidity and mortality, procedural risk, ...

Algorithms-Driven Optoelectronic Devices for Three-Dimensional Imaging.

Three-dimensional (3D) imaging captures spatial depth and multidimensional attributes, enabling precise scene reconstruction for diverse applications ...

Comparative evaluation of large language models for generating CAD-RADS 2.0-compliant diagnostic conclusions in cardiac CT reports.

OBJECTIVES: Coronary computed tomography angiography (CCTA) has become a cornerstone in non-invasive CAD diagnosis and risk stratification. To standar...

ThyroFusion: A Multi-modal Deep Learning Framework Integrating Vision and Language for Thyroid Nodule Malignancy Risk Assessment.

Accurate differentiation between benign and malignant thyroid nodules remains challenging in clinical practice. Current deep learning approaches predo...

Key factors of the deranged antiviral response in elderly patients with COVID-19: a machine-learning analysis.

Age is a well-known risk factor to develop severe viral respiratory infections, including severe COVID-19. This study aimed to identify the biological...

Deep learning-based segmentation and quantification of pulmonary masses on apparent diffusion coefficient maps: a multicentre reproducibility study.

OBJECTIVES: To develop and validate a deep learning model for automatic segmentation of pulmonary masses on apparent diffusion coefficient (ADC) maps ...

A generative AI framework unifies human multi-omics to model aging, metabolic health, and intervention response.

Understanding aging and complex diseases requires diverse data, ranging from molecular profiles to imaging and routine clinical tests. However, most m...