Geriatrics

Age-adjusted neurofilament light chain cutoffs for diagnosing neurodegenerative dementia: a two-threshold machine learning approach.

Clinical implementation of neurofilament light chain (NfL), a biomarker of neurodegeneration, remains challenging due to absence of reliable cutoffs and influence of confounding factors, particularly age. We aimed to develop an age-adjusted, two-threshold classification framework to support clinical interpretation of NfL in the neurodegenerative dementia diagnosis. We retrospectively enrolled subj...

MultiScaleKANNet: a hybrid CNN-KAN-transformer architecture for radiographic bone-loss risk stratification from knee X-rays.

Osteoporosis is underdiagnosed because dual-energy X-ray absorptiometry (DXA) is costly and scarce. We present MultiScaleKANNet, a hybrid deep-learning architecture for radiographic bone-loss risk stratification from routine knee X-rays, combining convolutional feature learning, learnable nonlinear transformations via Kolmogorov-Arnold Network (KAN) layers, and Transformer-based multi-scale attent...

Research on the efficacy of hybrid deep learning models for image-based classification of common oral conditions.

OBJECTIVE: To compare tuned end-to-end and hybrid deep learning strategies for image-based classification of common oral conditions under small and im...

ProtPhenoAge: Integrating plasma proteomics to predict Aging-Related disease Risks.

INTRODUCTION: Plasma proteins reflect the combined influence of both internal and external factors, making proteomics-based aging clocks a promising a...

Early Identification of Mobility Limitations in Community-Dwelling Middle-Aged and Older Adults: Development of a Prediction Model Based on a Prospective Cohort.

BACKGROUND: With the aging of the global population, preventing the onset of mobility limitations is considered a worldwide public health priority. OB...

AI-powered evaluation of dementia severity based on clinical data and visual scoring systems (MTA, ERICA, GCA) from MRI.

Dementia, particularly Alzheimer's disease (AD), is a growing concern in aging populations, with mild cognitive impairment (MCI) frequently progressin...

Multidimensional balance assessment and machine learning gait stability prediction in elderly women.

To develop and validate a comprehensive balance assessment scale specifically designed for elderly women and construct predictive models for gait stab...

Machine learning prediction for menopause women with low bone mass: a multicenter and retrospective study.

Early diagnosis of postmenopausal osteoporosis provides an opportunity to detect and prevent fractures. This study uses machine learning (ML) techniqu...

Identification of PTPRR gene associated with cirrhosis and sarcopenia based on bioinformatics and machine learning.

BACKGROUND: Cirrhosis and sarcopenia frequently coexist and are associated with poor clinical outcomes; however, their shared genetic basis remains in...

A deep hybrid CNN-BiLSTM-BiGRU architecture with explainability for mild cognitive impairment detection using EEG.

Accurate detection of Mild Cognitive Impairment (MCI) is critical for timely intervention and for slowing progression to Alzheimer's disease. Electroe...

Interpretable machine learning with SHAP analysis identifies redox-modulating dietary antioxidants for predicting accelerated biological aging.

BACKGROUND: Aging is a complex biological process characterized by progressive functional decline across multiple physiological systems, and biologica...

Early diagnosis of Alzheimer's disease through handwriting analysis and deep learning: A review.

Alzheimer's disease (AD) is one of the most prevalent neurodegenerative disorders worldwide, requiring early identification for timely intervention an...

Artificial Intelligence Applications in General Surgery in the United States of America: A Bibliometric Analysis.

BACKGROUND: Artificial intelligence (AI) is rapidly transforming surgical practice, with applications spanning preoperative planning, intraoperative g...

Integrating ConvNeXt tiny and radiomics in a nomogram to differentiate true progression from pseudoprogression in glioma.

PURPOSE: Differentiating true progression (TP) from pseudoprogression (PsP) in glioma is challenging due to overlapping enhancement patterns on conven...

A human-AI collaborative workflow for improved gross tumor volume delineation in esophageal cancer radiotherapy.

BACKGROUND: Esophageal cancer tumors exhibit complex and variable distribution. Due to differences in clinical experience, junior oncologists often sh...

An LC-MS-guided AI enabled serum molecule-interpretable SERS platform for exploratory metabolomic analysis in Alzheimer's disease.

Label-free surface-enhanced Raman spectroscopy (SERS) offers a promising avenue for rapid metabolic phenotyping in complex biofluids, yet its translat...

Food-derived bioactive peptides in gut-muscle Axis regulation: Potential and challenges from microbiota homeostasis to muscle metabolism remodeling.

The global population is aging at an accelerating pace, and sarcopenia has emerged as a central challenge to elderly health. Food-derived bioactive pe...

Development of AI-assisted 3D-printed degradable hydrogel microneedles for transdermal delivery of progesterone-loaded solid lipid nanoparticles: a novel approach to slowing Alzheimer's disease progression.

Progesterone (PG) is used to slow the progression of neurodegenerative diseases, particularly Alzheimer's disease (AD) in postmenopausal women. Howeve...

Heartbeats and hidden codes: Decoding cardiac aging with multi-omics and computational approaches.

Aging is a major risk factor for cardiovascular disease, yet the mechanisms driving age-related cardiac decline remain incompletely defined. Although ...

Examining developer perspectives on medical AI regulatory frameworks.

Regulatory frameworks ensure the trustworthiness of artificial intelligence in medicine (AI-MD). Yet, developers' perspectives on these frameworks rem...