Geriatrics

Temporal Dynamics of High-Frequency Oscillations in Alzheimer’s Disease: A Longitudinal Study in hAPP-J20 Mice

Alzheimer’s disease (AD) is characterized by progressive cognitive decline and increased seizure susceptibility; yet both the mechanistic and temporal links between AD and epileptogenesis remain poorly defined. In this study, we conducted a longitudinal analysis of epileptogenesis in relation to AD pathology using hAPP-J20 transgenic mice aged 9 to 27 weeks, encompassing the AD conversion phase. W...

Interpretable Aging Signatures in Human Retinal Cell Types Revealed by Single-Cell RNA Sequencing and Sparse Logistic Regression

To characterize cell type specific transcriptional changes during human retinal aging and develop machine learning model for cellular age discrimination in a Chinese cohort. Cross-sectional, laboratory-based observational study. Eighteen unfrozen retinas from 12 Chinese donors (9 young, 34-55y; 9 old, 68-92 y). Single-cell RNA sequencing (10x, v3.1) generated 223612 cells, batch-corrected with scV...

Machine learning prediction algorithms for 2- , 5- and 10-year risk of Alzheimer’s, Parkinson’s and dementia at age 65: a study using medical records from France and the UK General Practitioners

Leveraging machine learning on electronic health records offers a promising method for early identification of individuals at risk for dementia and ne...

GLUCOSE: A Distributional Reinforcement Learning Model for Optimal Glucose Control After Cardiac Surgery

This study introduces Glucose Level Understanding and Control Optimized for Safety and Efficacy (GLUCOSE), a distributional offline reinforcement lear...

Care Phenotypes In Critical Care

The Social Determinants of Health (SDoH) have long been recognised as significant drivers of health inequalities. Within healthcare settings, large EH...

Deep Learning Chest X-Ray Age, Epigenetic Aging Clocks and Associations with Age-Related Subclinical Disease in the Project Baseline Health Study

Chronological age is a cornerstone of medical decision-making but is limited because individuals age at different rates. We recently released an open-...

Predicting ADC Map Quality from T2-Weighted MRI: A Deep Learning Approach for Early Quality Assessment to Assist Point-of-Care

Poor quality prostate MRI images, especially ADC maps, can lead to missed lesions and unnecessary repeat scans. To address this issue, we aimed to dev...

End-to-end prediction of clinical outcomes in head and neck squamous cell carcinoma with foundation model-based multiple instance learning

Foundation models (FMs) show promise in medical AI by learning flexible features from large datasets, potentially surpassing handcrafted radiomics. Ou...

Image-based Explainable Artificial Intelligence Accurately Identifies Myelodysplastic Neoplasms Beyond Conventional Signs of Dysplasia

Evaluation of bone marrow morphology by experienced hematologists is key in the diagnosis of myeloid neoplasms, especially to detect subtle signs of d...

Brain Age Gap Reduction Following Physical Exercise Mirrors Negative Symptom Improvement in Schizophrenia Spectrum Disorders

Schizophrenia spectrum disorders (SSD) are associated with accelerated brain aging, reflected in an increased brain age gap. This gap serves as a biom...

SLaM Image Bank – a real-world diverse London cohort linking brain MRI to electronic mental health and dementia records for the development of clinical decision support tools using artificial intelligence

Rapid developments are occurring in artificial intelligence (AI) and machine learning (ML) applied to neuroimaging. To date, advances in this space ha...

Brain Age: A Promising Biomarker for Understanding Aging in the Context of Cognitive Reserve

Cognitive decline is a major concern in aging populations. Detecting it before clinical symptoms emerge remains a significant challenge. A precise, re...

Predicting Dementia in People with Parkinson’s Disease

Parkinson’s disease (PD) exhibits a variety of symptoms, with approximately 25% of patients experiencing mild cognitive impairment and 45% developing ...

VR-based Gamma Sensory Stimulation: A feasibility study

Alzheimer’s disease (AD) presents a critical global health challenge, with current therapies offering limited efficacy and safety in halting disease p...

WHITE-Net : White matter HyperIntensities Tissue Extraction using deep learning Network

Given the high prevalence of aging-associated cerebral small vessel disease in the general population, accurate detection of the related white matter ...

AI-Driven Early Detection of Severe Influenza in Jiangsu, China: A Deep Learning Model Validated Through The Design of Multi-Center Clinical Trials and Prospective Real-World Deployment

Influenza causes about 650,000 deaths worldwide each year, and the high mortality rate of severe cases is closely related to subjective bias in clinic...

Trust in large language model-based solutions in healthcare among people with and without diabetes: a cross-sectional survey from the Health in Central Denmark cohort

Large language models have gained significant public awareness since ChatGPT’s release in 2022. This study describes the perception of chatbot-assiste...

Generalizable Prediction of Alzheimer Disease Pathologies with a Scalable Annotation Tool and an High-Accuracy Model

Characterizing the cardinal neuropathologies in Alzheimer disease (AD) can be laborious, time consuming, and susceptible to intra- and inter-observer ...

Do Language Models Think Like Doctors?

While large language models (LLMs) are being increasingly deployed for clinical decision support, existing evaluation methods like medical licensing e...

CT-based Osteoporosis Classification and Bone-Muscle Interaction Mapping Using Multiple Interpretable Machine Learning Models with the BMINet Framework

Osteoporosis progresses through stages characterized by declining bone mineral density, vertebral deterioration, and muscle atrophy, with bone-muscle ...