Alzheimer's Disease

Assessment of Large Language Models for Tracheostomy Care in Pediatrics: ChatGPT vs Claude.

INTRODUCTION: This study aimed to evaluate the accuracy, completeness, clarity, and relevance of responses provided by two freely available large language models (LLMs)-ChatGPT-4.o and Claude 4.0 Sonnet-to caregiver-focused questions about pediatric tracheostomy. METHODS: Seventeen clinically relevant questions were submitted to each LLM, and responses were evaluated by nine pediatric otolaryngolo...

Predicting Peptide Aggregation with Protein Language Model Embeddings.

Amyloid fibrils, a form of peptide aggregates, are associated with multiple diseases and hinder the development of therapeutics. The experimental characterization of aggregating peptides is resource-intensive, and data are scarce, limiting the development of accurate models. We present a deep-learning model, PALM (Predicting Aggregation with Language Model embeddings), which uses transfer learning...

Amyloid-beta statuses prediction with free water MR imaging features in Alzheimer's disease using machine learning models.

Development of a community home-based dual-supplier cooperation care model for people with dementia based on an intelligent decision-assistance system: protocol of a 1-year randomised controlled trial in China.

INTRODUCTION: Dementia imposes significant care and financial burdens on families and countries globally. While high-quality home-based care is crucia...

Establishing a Diagnostic Model Based on Plasma CDR1as and Alpha-Synuclein for Mild Cognitive Impairment in Type 2 Diabetes.

Emerging evidence implicates cerebellar degeneration-related protein 1 antisense transcript (CDR1as) and alpha-synuclein (α-Syn) in diabetes and cogni...

Data-driven thresholds for standardized classification of severe Alzheimer's disease neuropathology using digital neuropathology.

Alzheimer's disease neuropathological changes (ADNC)-operationalized with semi-quantitative parameters-represent the consensus-based gold standard for...

Dementia screening with the Rivermead Behavioural Memory Test: A machine learning analysis.

BackgroundWith the advent of anti-amyloid-β monoclonal antibody therapies and the growing societal burden of dementia, early identification of Alzheim...

Brain PET in the era of anti-amyloid-β antibody therapy for Alzheimer disease.

Here the current and emerging roles of brain positron emission tomography (PET) in Alzheimer's disease (AD) in the era of anti-amyloid-β antibody ther...

Adaptive neighborhood aggregation graph neural network for early diagnosis of Alzheimer's disease.

Early diagnosis of Alzheimer's disease (AD) is crucial for timely intervention but remains challenging due to subtle and heterogeneous brain alteratio...

A frontotemporal dementia-like phenotype in schizophrenia: links to striatal dopamine and iron accumulation.

Some schizophrenia patients share characteristics with behavioral variant frontotemporal dementia (bvFTD) including gray matter volume (GMV) similarit...

MMP9 as a shared immune-related gene in Alzheimer's and Huntington's diseases: a cross-tissue transcriptomic analysis.

Alzheimer's disease (AD) and Huntington's disease (HD) share neuroinflammatory mechanisms, yet their specific immune microenvironments remain poorly u...

Causal ordinal connections based characterization of weighted effective brain network for schizophrenia detection.

The human brain is responsible for a wide range of a person's behavioral and cognitive capabilities. The functionality of the brain is affected by var...

Alzheimer's disease with progression analysis using a novel dilated convolutional attention based long short term memory model.

Alzheimer's disease (AD) is an irreversible neurodegenerative syndrome that affects memory, cognitive abilities and behaviour. Detecting AD in the ear...

Baseline brain volumes predict cognitive decline more robustly than atrophy rates: Evidence for brain reserve.

The concept of brain reserve offers a framework for understanding the mechanisms of cognitive resilience in later life. This study investigated whethe...

Association of MRI-Visible Perivascular Spaces With Longitudinal Cognitive Decline Over a Decade.

BACKGROUND AND OBJECTIVES: Cerebral small vessel disease (SVD) is the most common vascular contributor to dementia. SVD markers often coexist, contrib...

Transferability of a US claims-based machine learning model for ATTRwt-CM identification: a retrospective evaluation in a German setting.

Cardiac amyloidosis (CA), a fatal and progressive cardiomyopathy is characterized by amyloid deposition within the myocardium. The main forms of CA in...

Olfactory radiomics signatures link pTau217 to cognitive impairment in probable Alzheimer's disease: a multi-cohort machine learning study.

Large Language Models for Cardiac MRI Diagnosis Based on Standardized Text Descriptions.

BACKGROUND: MRI is important for cardiac disease evaluation, but accurate diagnosis remains challenging in less experienced centers. Although large la...

Leveraging routine clinical data for dementia risk prediction using machine learning.

BackgroundEarly diagnosis of dementia is essential for enabling timely interventions that may slow disease progression, improve patient outcomes, and ...

AI in Atomic Force Microscopy: Advancing Biological Nanoscale Imaging and Autonomous Discovery.

Atomic force microscopy (AFM) enables label-free nanoscale imaging and nanomechanical profiling but remains constrained by low throughput, operator de...