Geriatrics

Explainable artificial intelligence for neuroimaging-based dementia diagnosis and prognosis

INTRODUCTION: Artificial intelligence and neuroimaging enable accurate dementia prediction, but ‘black box’ models can be difficult to trust. Explainable artificial intelligence (XAI) describes techniques to understand model behaviour and the influence of features, however deciding which method is most appropriate is non-trivial. Vision transformers (ViT) have also gained popularity, providing a s...

CONORM: Context-Aware Entity Normalization for Adverse Drug Event Detection

Adverse drug events (ADEs) are a critical aspect of patient safety and pharmacovigilance, with significant implications for patient outcomes and public health monitoring. The increasing availability of electronic health records, social media, and online patient forums provides valuable yet challenging unstructured data sources for ADE surveillance. To address these challenges, we introduce CONORM,...

Leveraging artificial Intelligence and online psychotherapy to achieve efficient and coordinated services within a healthcare setting: A quality improvement initiative

This study aimed to implement an artificial intelligence-assisted psychiatric triage program, assessing its impact on efficiency and resource optimiza...

Transcriptomic analyses of human brains with Alzheimer’s disease identified dysregulated epilepsy-causing genes

Alzheimer’s Disease (AD) patients at multiple stages of disease progression have a high prevalence of seizures. However, whether AD and epilepsy share...

DUNE: a versatile neuroimaging encoder captures brain complexity across three major diseases: cancer, dementia and schizophrenia

Magnetic resonance images (MRI) of the brain exhibit high dimensionality that pose significant challenges for computational analysis. While models pro...

Investigating the causal network of dementia by employing a causal discovery approach combined with natural language processing models

Comprehensively studying modifiable risk factors altogether to explore how they contribute to dementia mechanism is imperative for effective intervent...

Enhancing Brain Age Estimation Under Uncertainty: A Spectral-normalized Neural Gaussian Process Approach Utilizing 2.5D Slicing

Brain age gap, the difference between estimated brain age and chronological age via magnetic resonance imaging, has emerged as a pivotal biomarker in ...

Characterizing multivariate regional hubs for schizophrenia classification, sex differences, and brain age estimation using explainable AI

To investigate multivariate regional patterns for schizophrenia (SZ) classification, sex differences, and brain age by utilizing structural MRI, demog...

Multi-organ metabolome biological age implicates cardiometabolic conditions and mortality risk

Biological aging clocks across organs and omics data, including clinical phenotypes, neuroimaging, proteomics, and epigenetics, have proven instrument...

Leveraging functional annotations to map rare variants associated with Alzheimer’s disease with gruyere

The increasing availability of whole-genome sequencing (WGS) has begun to elucidate the contribution of rare variants (RVs), both coding and non-codin...

AgeNet-SHAP: An explainable AI approach for optimally mapping multivariate regional brain age and clinical severity patterns in Alzheimer’s disease

Age is a significant risk factor for mild cognitive impairment (MCI) and Alzheimer’s disease (AD) and identifying brain age patterns is critical for c...

Interpretable multivariate survival models: Improving predictions for conversion from mild cognitive impairment to Alzheimer’s disease (AD) via data fusion and machine learning

Accurately predicting which individuals with mild cognitive impairment (MCI) will progress to Alzheimer’s disease (AD) can improve patient care. This ...

Unravelling the Complex Inflammatory Landscape of COVID-19 infection: A Pathway to Biomarkers Identification in Infection-Associated Delirium in the ICU

Delirium is a serious complication in patients with COVID-19-related acute respiratory distress syndrome (ARDS) admitted to the intensive care unit (I...

PREACT-digital: Study protocol for a longitudinal, observational multi-center study on wearable- and EMA- based predictors of non-response to CBT for internalizing disorders

Despite CBT’s status as a first-line treatment, a substantial proportion of patients does not experience sufficient symptom relief. Recent advances in...

Perceptions and Insights: A Qualitative Assessment of an AI-Assisted Psychiatric Triage System Implemented in an Outpatient Hospital Setting

The Canadian healthcare system is approaching a breaking point. With mental health being a leading cause of disability, innovative solutions are neces...

Precise perivascular space segmentation on magnetic resonance imaging from Human Connectome Project-Aging

Perivascular spaces (PVS) are cerebrospinal fluid-filled tunnels around brain blood vessels, crucial for the functions of the glymphatic system. Chang...

Integration of Deep Learning Annotations with Functional Genomics Improves Identification of Causal Alzheimer’s Disease Variants

Genetic variants associated with Alzheimer’s disease (AD) through genome-wide association studies (GWAS) are challenging to interpret because most lie...

Spine age estimation using deep learning in lateral spine radiographs and DXA VFA to predict incident fracture and mortality

Spine age estimated from lateral spine radiographs and DXA vertebral fracture assessments (VFAs) could be associated with fracture and mortality risk....

Artificial Intelligence Prediction of Age from Echocardiography as a Marker for Cardiovascular Disease

Accurate understanding of biological aging and the impact of environmental stressors is crucial for understanding cardiovascular health and identifyin...

Foundation models for generalizable electrocardiogram interpretation: comparison of supervised and self-supervised electrocardiogram foundation models

The 12-lead electrocardiogram (ECG) remains a cornerstone of cardiac diagnostics, yet existing artificial intelligence (AI) solutions for automated in...