Geriatrics

Modality-Aware Discriminative Fusion Network for Integrated Analysis of Brain Imaging Genomics.

Mild cognitive impairment (MCI) represents an early stage of Alzheimer's disease (AD), characterized by subtle clinical symptoms that pose challenges for accurate diagnosis. The quest for the identification of MCI individuals has highlighted the importance of comprehending the underlying mechanisms of disease causation. Integrated analysis of brain imaging and genomics offers a promising avenue fo...

How Can Anomalous-Diffusion Neural Networks Under Connectomics Generate Optimized Spatiotemporal Dynamics.

Spatiotemporal dynamics in the brain have been recognized as strongly related to the formation of perceived and cognitive diseases, such as delusions and hallucinations in Alzheimer's disease. However, two practical considerations are rarely mentioned in related mechanism research: the connectomics networking and the anomalous diffusion generated by the complex medium between neurons and the compl...

Deep Profiling of Oocyte Aging Enabled by Simple One-Step Vial-Based Pretreatment and Single-Cell Proteomics.

Single-cell proteomics is a pivotal technology for studying cellular phenotypes, offering unparalleled insights into cellular heterogeneity and dynami...

Exploring Suitability of Low-Severity Rating Hospital Incident Reports for Machine Learning.

Electronic incident reporting is a key quality and a safety process for healthcare organizations that assists in evaluating performance and informing ...

Machine Learning Multimodal Model for Delirium Risk Stratification.

IMPORTANCE: Automating the identification of risk for developing hospital delirium with models that use machine learning (ML) could facilitate more ra...

Gender Authorship Among Urology Artificial Intelligence Publications: A 10-Year Retrospective Analysis.

We aim to characterize gender authorship in urology-related artificial intelligence (AI) research. A retrospective review was performed using MEDLINE,...

Intelligent predictive risk assessment and management of sarcopenia in chronic disease patients using machine learning and a web-based tool.

BACKGROUND: Individuals with chronic diseases are at higher risk of sarcopenia, and precise prediction is essential for its prevention. This study aim...

Alzheimer's disease knowledge graph enhances knowledge discovery and disease prediction.

OBJECTIVE: To construct an Alzheimer's Disease Knowledge Graph (ADKG) by extracting and integrating relationships among Alzheimer's disease (AD), gene...

Using artificial intelligence-based software for an unbiased discrimination of immune cell subtypes in the fracture hematoma and bone marrow of non-osteoporotic and osteoporotic mice.

It is well established that the early inflammatory response following fracture is essential for initiating subsequent bone regeneration. An imbalance ...

Evaluating the Chinese versions of delirium assessment scales: a diagnostic systematic review.

BACKGROUND: The purpose of this study is to examine the validity, reliability and methodological quality of delirium scales that have been translated ...

AI in Home Care-Evaluation of Large Language Models for Future Training of Informal Caregivers: Observational Comparative Case Study.

BACKGROUND: The aging population presents an accomplishment for society but also poses significant challenges for governments, health care systems, an...

A novel diagnosis method utilizing MDBO-SVM and imaging genetics for Alzheimer's disease.

Alzheimer's disease (AD) is the most common neurodegenerative disorder, yet its underlying mechanisms remain elusive. Early and accurate diagnosis is ...

Biological age prediction in schizophrenia using brain MRI, gut microbiome and blood data.

The study of biological age prediction using various biological data has been widely explored. However, single biological data may offer limited insig...

Therapeutic potential of enzymes, neurosteroids, and synthetic steroids in neurodegenerative disorders: A critical review.

Neurodegenerative disorders present a significant challenge to healthcare systems, mainly due to the limited availability of effective treatment optio...

A divide-and-conquer approach based on deep learning for long RNA secondary structure prediction: Focus on pseudoknots identification.

The accurate prediction of RNA secondary structure, and pseudoknots in particular, is of great importance in understanding the functions of RNAs since...

Generative artificial intelligence, integrative bioinformatics, and single-cell analysis reveal Alzheimer's genetic and immune landscape.

The research aims to understand Alzheimer's genetic and immune landscapes using the amalgamation of three technologies: artificial intelligence (GenAI...

Enhanced EEG-based Alzheimer's disease detection using synchrosqueezing transform and deep transfer learning.

The most prevalent type of dementia and a progressive neurodegenerative disease, Alzheimer's disease has a major influence on day-to-day functioning d...

A review of multimodal fusion-based deep learning for Alzheimer's disease.

Alzheimer's Disease (AD) as one of the most prevalent neurodegenerative disorders worldwide, characterized by significant memory and cognitive decline...

Vascular-related biological stress, DNA methylation, allostatic load and domain-specific cognition: an integrated machine learning and causal inference approach.

BACKGROUND: Vascular disease in aging populations spans a wide range of disorders including strokes, circulation disorders and hypertension. As indivi...

Interpretable machine learning model for predicting delirium in patients with sepsis: a study based on the MIMIC data.

OBJECTIVE: The aim of this study was to construct interpretable machine learning models to predict the risk of developing delirium in patients with se...