Geriatrics

Determining the ground truth for the prediction of delirium in adult patients in acute care: a scoping review.

OBJECTIVE: Delirium is a severe condition, often underreported and linked to adverse outcomes such as increased mortality and prolonged hospitalization. Despite its significance, delirium prediction is often hindered by underreporting and inconsistent labeling, highlighting the need for models trained on reliably labeled data (ground truth). This review examines (i) practices for determining label...

Applications of artificial intelligence in abdominal imaging.

The rapid advancements in artificial intelligence (AI) carry the promise to reshape abdominal imaging by offering transformative solutions to challenges in disease detection, classification, and personalized care. AI applications, particularly those leveraging deep learning and radiomics, have demonstrated remarkable accuracy in detecting a wide range of abdominal conditions, including but not lim...

ElixirSeeker: A Machine Learning Framework Utilizing Fusion Molecular Fingerprints for the Discovery of Lifespan-Extending Compounds.

Despite the growing interest in developing anti-aging drugs, high costs and low success rates of traditional drug discovery methods pose significant c...

ASO Author Reflections: Machine Learning for Postoperative Frailty Prediction in NSCLC-From Model Development to Clinical Translation.

Computational Risk Stratification of Preclinical Alzheimer's in Younger Adults.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that often begins decades before clinical symptoms manifest. Early detection rem...

Comprehensive Analysis of the Role of Metabolic Features in Osteoporosis: A Multi-Omics Analysis.

PURPOSE: This study aims to comprehensively explore the metabolic features related to the pathogenesis of osteoporosis (OP) through multi-omics analys...

Prediction of mild cognitive impairment using blood multi-omics data.

Mild cognitive impairment (MCI) represents an initial phase of memory or other cognitive function decline and is viewed as an intermediary stage betwe...

Speech-based digital cognitive assessments for detection of mild cognitive impairment: Validation against paper-based neurocognitive assessment scores.

BackgroundCognitive decline in Alzheimer's disease (AD) often includes speech impairments, where subtle changes may precede clinical dementia onset. A...

Translational computerized clinical decision support systems for Alzheimer's disease: A systematic review.

BackgroundAlzheimer's disease (AD), marked by progressive memory loss and cognitive decline, poses diagnostic challenges due to its multifactorial nat...

Predicting Mortality in Atrial Fibrillation Patients Treated with Direct Oral Anticoagulants: A Machine Learning Study Based on the MIMIC-IV Database.

Atrial fibrillation (AF) is a common arrhythmia linked to increased mortality and significant healthcare burden, especially in the elderly. Direct Or...

Epidemiology and survival of patients with primary lymphoma of bone: a large retrospective cohort study.

Primary lymphoma of bone (PLB) is a rare extranodal lymphoma, and its epidemiology and prognosis remain controversial. We conducted a retrospective an...

Bridging Genomic Research Disparities in Osteoporosis GWAS: Insights for Diverse Populations.

PURPOSE OF REVIEW: Genome-wide association studies (GWAS) have significantly advanced osteoporosis research by identifying genetic loci associated wit...

Development and validation of a hypoxemia prediction model in middle-aged and elderly outpatients undergoing painless gastroscopy.

Hypoxemia is a common complication associated with anesthesia in painless gastroscopy. With the aging of the social population, the number of cases of...

Process management method in head and neck cancer patient care.

Management of patients with head and neck cancer (HNC) is a complex process that involves extensive knowledge on (at least) the discipline of surgery,...

Renal Transplant Survival Prediction From Unsupervised Deep Learning-Based Radiomics on Early Dynamic Contrast-Enhanced MRI.

RATIONALE AND OBJECTIVES: End-stage renal disease is characterized by an irreversible decline in kidney function. Despite a risk of chronic dysfunctio...

In-silico evaluation of aging-related interventions using omics data and predictive modeling.

A major challenge in aging research is identifying interventions that can improve lifespan and health and minimize toxicity. Clinical studies cannot u...

A Convolutional Mixer-Based Deep Learning Network for Alzheimer's Disease Classification from Structural Magnetic Resonance Imaging.

Alzheimer's disease (AD) is a neurodegenerative disorder that severely impairs cognitive function across various age groups, ranging from early to la...

Advancements in Machine Learning for Precision Diagnostics and Surgical Interventions in Interconnected Musculoskeletal and Visual Systems.

Artificial intelligence (AI) is reshaping precision medicine by revealing diagnostic links between ocular biomarkers and systemic musculoskeletal diso...

Performance of Machine Learning Models in Predicting 30-Day General Medicine Readmissions Compared to Traditional Approaches in Australian Hospital Setting.

: Hospital readmissions are a key quality metric impacting both patient outcomes and healthcare costs. Traditional logistic regression models, includi...

Cell-TRACTR: A transformer-based model for end-to-end segmentation and tracking of cells.

Deep learning-based methods for identifying and tracking cells within microscopy images have revolutionized the speed and throughput of data analysis....