Peripheral Artery Disease

A psychologically interpretable artificial intelligence framework for the screening of loneliness, depression, and anxiety.

Negative emotions such as loneliness, depression, and anxiety (LDA) are prevalent and pose significant challenges to emotional well-being. Traditional methods of assessing LDA, reliant on questionnaires, often face limitations because of participants' inability or potential bias. This study introduces emoLDAnet, an artificial intelligence (AI)-driven psychological framework that leverages video-re...

DermaSynth: Rich Synthetic Image-Text Pairs Using Open Access Dermatology Datasets

A major barrier to developing vision large language models (LLMs) in dermatology is the lack of large image--text pairs dataset. We introduce DermaSynth, a dataset comprising of 92,020 synthetic image--text pairs curated from 45,205 images (13,568 clinical and 35,561 dermatoscopic) for dermatology-related clinical tasks. Leveraging state-of-the-art LLMs, using Gemini 2.0, we used clinically rela...

Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled Data

Amortized Bayesian inference (ABI) with neural networks can solve probabilistic inverse problems orders of magnitude faster than classical methods. ...

Learning Hemodynamic Scalar Fields on Coronary Artery Meshes: A Benchmark of Geometric Deep Learning Models

Coronary artery disease, caused by the narrowing of coronary vessels due to atherosclerosis, is the leading cause of death worldwide. The diagnostic...

Multi-View Transformers for Airway-To-Lung Ratio Inference on Cardiac CT Scans: The C4R Study

The ratio of airway tree lumen to lung size (ALR), assessed at full inspiration on high resolution full-lung computed tomography (CT), is a major ri...

An Intra- and Cross-frame Topological Consistency Scheme for Semi-supervised Atherosclerotic Coronary Plaque Segmentation

Enhancing the precision of segmenting coronary atherosclerotic plaques from CT Angiography (CTA) images is pivotal for advanced Coronary Atheroscler...

Towards Iris Presentation Attack Detection with Foundation Models

Foundation models are becoming increasingly popular due to their strong generalization capabilities resulting from being trained on huge datasets. T...

IPDN: Image-enhanced Prompt Decoding Network for 3D Referring Expression Segmentation

3D Referring Expression Segmentation (3D-RES) aims to segment point cloud scenes based on a given expression. However, existing 3D-RES approaches fa...

Targeted Enzymatic Fragmentation of Lipoprotein(a) via Kringle IV Domains: A Clearance-Enhancing Therapeutic Strategy for Cardiovascular Disease

Elevated lipoprotein(a) [Lp(a)] is an independent, genetically determined risk factor for atherosclerotic cardiovascular disease (ASCVD). Its unique a...

Comparison of Brain Age Algorithms in Bipolar Disorder

Advances in computational methods have accelerated the application of machine learning to analyze large complex biological data. By applying machine l...

Benchmarking datasets for machine learning in protein function prediction

Remarkable progress has been achieved by machine learning, particularly in accurate prediction of protein tertiary structures. Despite these advances,...

Spatially resolved proteomic signatures of atherosclerotic carotid artery disease

Atherosclerotic plaque rupture remains a leading cause of adverse cardiovascular events, yet the molecular drivers of plaque vulnerability are incompl...

A Machine-Learning Approach to Finding Gene Target Treatment Options for Long COVID

Long COVID, also known as post-acute sequelae of SARS-CoV-2 infection (PASC), encompasses a range of symptoms persisting for weeks or months after the...

Impact of Aspirin Therapy on Progression of Thoracic and Abdominal Aortic Aneurysms

Aortic aneurysms, including abdominal (AAA) and thoracic (TAA), pose significant challenges due to their rupture risk and complex pathophysiology. Whi...

Modulated smooth muscle cells accumulate late in human coronary atherosclerosis and are temporally and spatially linked to necrotic core formation

Proliferation of arterial smooth muscle cells (SMCs) and their modulation to alternative mesenchymal phenotypes is a central mechanism in the growth o...

Optimized Feature Selection and Advanced Machine Learning for Stroke Risk Prediction in Revascularized Coronary Artery Disease Patients

Coronary artery disease (CAD) is a leading cause of mortality, with stroke being a major complication following coronary revascularization procedures ...

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....

Intraplaque haemorrhage quantification and molecular characterisation using attention based multiple instance learning

Intraplaque haemorrhage (IPH) represents a critical feature of plaque vulnerability as it is robustly associated with adverse cardiovascular events, i...

Clinical phenotypes in hypertension: a data-driven approach to risk stratification and outcome prediction

Hypertension (HTN) is a major contributor to cardiovascular (CV) morbidity and mortality. Its heterogeneity complicates risk stratification. Unsupervi...

Extracting Carotid Stenosis Severity from Clinical Notes Using Natural Language Processing: Development, Validation, and Application in a Nationwide Veteran Cohort

Carotid stenosis, which is atherosclerotic narrowing of the extracranial carotid arteries, is an important risk factor for ischemic stroke. The preval...