Geriatrics

Medical intelligence vs. artificial intelligence - How psychiatrists arrive at treatment algorithms.

The rise of artificial intelligence and computational methods in clinical decision-making allows for...

Integrated metabolomics and machine learning identify potential biomarkers and metabolism-related targets for MASLD in older adults.

BACKGROUND: Given the high prevalence and serious health threats of Metabolic dysfunction-associated...

A systems approach identifies MERTK as a therapeutic vulnerability in ZFTA-RELA-driven ependymomas.

Ependymomas (EPN) are rare central nervous system tumors that account for approximately 10% of intra...

Photoswitches for ion channel regulation: expanding the scope of phototherapy through computational chemistry.

The development of ion channel phototherapy using azobenzene-based photoswitchable molecules represe...

Systems Biology of Aging, Metabolism, and Mitochondria.

Since the beginning of this century, the emergence of systems biology, driven by technological, info...

Unsupervised Disentanglement of Brain Heterogeneity for Identifying Subtypes of Alzheimer's Disease.

Neuroanatomical heterogeneity in Alzheimer's disease (AD) hinders precision diagnosis and treatment,...

Understanding patient experience during Lokomat rehabilitation in children and adolescents: a clinical observational study combining self-evaluation and physiological metrics.

OBJECTIVES: To examine the emotional, cognitive and dispositional experience of children and adolesc...

Alzheimer's disease prediction using deep learning and XAI based interpretable feature selection from blood gene expression data.

Alzheimer's disease (AD), a type of neurodegenerative disorder, has seen an increase in cases over t...

Machine learning evaluation of the discriminative ability of Castelli Risk Index-I and other non-traditional lipid indices for sarcopenia: a cross-sectional study based on CHARLS.

Health-oriented sleep states: making sleep states reflect health conditions.

STUDY OBJECTIVES: The rich information in sleep offers insights into brain function and overall heal...

Elucidating the toxicological impact and mechanism of plasticizers exposure on Alzheimer's disease through network toxicology and molecular docking.

This study aimed to explore the underlying mechanisms and key targets of widely used plasticizers, i...

Prenatal alcohol exposure and the retrosplenial cortex: Structural and functional mechanisms across species.

The retrosplenial cortex (RSC) is a structurally and functionally complex hub with broad connectivit...

Exploring the potential of explainable deep learning for EEG-based cognitive decline prediction.

OBJECTIVE: Detecting Alzheimer's disease (AD) at an early stage is essential for administering effec...

Reactive Neural Network Potential Developed for Asphalt Aging Systems Through Active Learning and Enhanced Sampling.

The atomic-scale mechanisms of asphalt oxidative aging remain poorly understood due to the chemical ...

Research on fall prediction in elderly patients with chronic diseases based on explainable machine learning: an aging perspective.

Integrating standard and native spaces for radiomics and brain network analysis in Alzheimer's disease diagnosis and prognosis.

INTRODUCTION: Structural MRI analysis for Alzheimer's disease (AD) is limited by balancing group-lev...

Glymphatic dysfunction in trigeminal neuralgia: A multimodal MRI study.

BACKGROUND: Trigeminal neuralgia (TN) has traditionally been attributed to peripheral neurovascular ...

[Key Drivers of PM2.5 in Qingdao from 2013 to 2023 Using an Interpretable Machine Learning Model].

To elucidate the deceleration trend in PM2.5 concentration reduction and its formation mechanisms， t...

Factors Associated with Machine Learning-Based Predictions of Retinal Aging Using Teleretinal Screening Images from Patients with Diabetes.

PURPOSE: To identify factors associated with accelerated retinal aging based on machine learning pre...

AI-driven biomarker learning for the early diagnosis of neurodegenerative diseases: ABLEDx.

BACKGROUND: Tears are an easily accessible biofluid that reflects both emotional states and disease ...

An interpretable machine learning framework with data-informed imaging biomarkers for diagnosis and prediction of Alzheimer's disease.

Machine learning methods based on imaging and other clinical data have shown great potential for imp...