Geriatrics

A Habitat Imaging-Based Radiomics and Deep Learning Fusion for Preoperative Prediction of Lymphovascular Invasion in Invasive Breast Cancer: A Multicenter Study.

BACKGROUND: Lymphovascular invasion (LVI) is a critical prognostic factor in invasive breast cancer; however, reliable preoperative prediction remains challenging because of the lack of non-invasive and accurate assessment tools. Ultrasound-based radiomics and deep learning have shown promise, but conventional single-modality approaches often fail to capture intratumoral heterogeneity, thereby lim...

Biological aging clocks as biomarkers of human aging: Biological basis, methodological design, and epidemiological implications.

Biological age (BA) has been proposed as a complementary construct to chronological age (CA) for quantifying interindividual heterogeneity in aging trajectories. Biological aging clocks (BACs) integrate molecular, clinical and multi-omics biomarkers to estimate aging-related phenotypes beyond CA. This narrative review critically examines the biological foundations, statistical methodologies, inter...

Ultrafast (0.5-Minute) Deep Learning Based Choroid Plexus Segmentation: Links to Cognitive Impairment and Glymphatic Function.

BACKGROUND AND PURPOSE: Choroid plexus volume (CPV) may reflect cognitive impairment and glymphatic dysfunction. However, its clinical use is limited ...

Generative Brain Priors-Driven Self-Regulated and Clinically-Guided Multimodal Fusion for Early Alzheimer's Disease Diagnosis.

Alzheimer's disease (AD) and mild cognitive impairment (MCI) require accurate early diagnosis to support timely clinical intervention and disease mana...

Cell surface CD11c as a neutrophil aging marker molecule.

Neutrophils exhibit substantial functional heterogeneity shaped by both developmental stage and cellular maturation, but their mechanisms remain incom...

Multitargeted drug strategies for Alzheimer's and Parkinson's diseases.

Neurodegenerative diseases, including Alzheimer's disease (AD) and Parkinson's disease (PD), are multifactorial diseases that are characterized by sev...

Machine Learning-Driven Bioprospecting of Cholinergic Medicinal Plants for Putative Leads Against Butyrylcholinesterase Towards Alzheimer's Care.

Butyrylcholinesterase (BChE) plays a key role in preserving appropriate cholinergic neurotransmission that is essentially altered in the brains of adv...

Deep learning approaches to predict femoral neck T-score and osteopenia/osteoporosis status from wrist accelerometry data.

Osteoporosis is a prevalent condition with substantial health and economic implications. Although physical activity is associated with bone health, th...

Gut microbiota and blood biomarkers as correlating factors in patients with postoperative delirium: analysis of three prospective observational studies.

Postoperative delirium is associated with both gut microbiota alterations and Tau phosphorylation; however, how these factors interact and jointly con...

The impact of frailty and its changes on the development of motoric cognitive risk syndrome in middle-aged and older adults.

BACKGROUND: Previous research links frailty to cognitive decline, but the relationship between frailty and motoric cognitive risk syndrome (MCR), a de...

Early Retinal UCHL1 Dysregulation Coupled With Synaptic Loss Reflects Alzheimer's Disease Severity.

Synaptic dysfunction is a major driver of cognitive decline in Alzheimer's disease (AD), yet its extent and molecular basis in the retina remain poorl...

Development and validation of a machine learning-based model for predicting fall-related injury risk in hospitalized patients.

BACKGROUND: Falls are among the most common adverse events in hospitalized patients, with about 30% leading to injury. We developed a machine learning...

Infection with Western equine encephalitis virus causes severe regional glial reactivity and neurodegeneration in the hippocampus with progressive accumulation of amyloid-β.

Encephalitic alphaviruses such as Western equine encephalitis virus (WEEV) result in significant morbidity through acute viremia and postencephalitic ...

Machine learning-based prediction of fall within 6 months of stroke onset: A prospective study.

OBJECTIVE: To develop and evaluate machine learning-based models for predicting fall risk within 6 months of stroke onset. METHODS: This prospective s...

Beyond predictive performance: Interpretability challenges and feature importance bias in XGBoost-based readmission models.

Song et al. report a machine-learning framework based on the eXtreme Gradient Boosting (XGBoost) algorithm for predicting 1-year unplanned readmission...

Frequency-enhanced AutoEncoding decomposed transformer (FEADformer) for total phosphorus prediction in industrial recirculating cooling water systems.

Accurate total phosphorus (TP) control is critical for the stable operation of industrial recirculating cooling water (RCW) systems. However, industri...

Machine learning-based screening model for osteoporosis in Chinese postmenopausal women: a nationwide study with prospective fracture validation.

UNLABELLED: This study develops a machine learning model to predict osteoporosis in Chinese postmenopausal women. The model was trained using the larg...

A comparative study of vision transformer architectures for the detection of Alzheimer's disease using magnetic resonance images.

Alzheimer's disease is a neurodegenerative disease that affects millions of people worldwide. With the increasing global elderly population, early and...

Dementia Etiology Diagnosis via Collaborative Meta Knowledge Enhancement.

Although artificial intelligence (AI) has shown promising performance in several medical tasks, accurate dementia etiology diagnosis with AI remains c...

AI-based segmentation of occult cervical lymph node metastases: potential reduction of cytokeratin staining.

BACKGROUND: Detection of occult cervical lymph node metastases is critical for accurate staging and treatment planning in oral cavity squamous cell ca...