Environmental Health

Multimodal Lead-Specific Modeling of ECG for Low-Cost Pulmonary Hypertension Assessment

Pulmonary hypertension (PH) is frequently underdiagnosed in low- and middle-income countries (LMICs) primarily due to the scarcity of advanced diagnostic tools. Several studies in PH have applied machine learning to low-cost diagnostic tools like 12-lead ECG (12L-ECG), but they mainly focus on areas with limited resources, overlooking areas with no diagnostic tools, such as rural primary healthc...

Artificial Intelligence-Based Personalization of Treatment Regimen for Hair Loss: A 6-Month Clinical Trial.

Hair loss affects up to 50% of women and 80% of men. The high costs and wait times for professional consultations lead many to seek one-size-fits-all solutions that are frequently ineffective. This study tested an artificial intelligence (AI) model for customizing non-medicated hair loss treatments. In a 24-week trial, 38 women with self-reported hair thinning received personalized product kits ba...

Analyzing the temporal dynamics of linguistic features contained in misinformation

Consumption of misinformation can lead to negative consequences that impact the individual and society. To help mitigate the influence of misinforma...

Zero-Shot Defense Against Toxic Images via Inherent Multimodal Alignment in LVLMs

Large Vision-Language Models (LVLMs) have made significant strides in multimodal comprehension, thanks to extensive pre-training and fine-tuning on ...

Knowledge-enhanced Multimodal ECG Representation Learning with Arbitrary-Lead Inputs

Recent advances in multimodal ECG representation learning center on aligning ECG signals with paired free-text reports. However, suboptimal alignmen...

Arrhythmia Classification from 12-Lead ECG Signals Using Convolutional and Transformer-Based Deep Learning Models

In Romania, cardiovascular problems are the leading cause of death, accounting for nearly one-third of annual fatalities. The severity of this situa...

TabulaTime: A Novel Multimodal Deep Learning Framework for Advancing Acute Coronary Syndrome Prediction through Environmental and Clinical Data Integration

Acute Coronary Syndromes (ACS), including ST-segment elevation myocardial infarctions (STEMI) and non-ST-segment elevation myocardial infarctions (N...

Unveiling Institution-Specific Bias in Pathology Foundation Models: Detriments, Causes, and Potential Solutions

Pathology foundation models (PFMs) extract valuable discriminative features from images for downstream clinical tasks. PFMs have simplified the deve...

Detecting Long QT Syndrome and First-Degree Atrioventricular Block using Single-Lead AI-ECG: A Multi-Center Real-World Study

Home-based single-lead AI-ECG devices have enabled continuous, real-world cardiac monitoring. However, the accuracy of parameter calculations from s...

MAGO-SP: Detection and Correction of Water-Fat Swaps in Magnitude-Only VIBE MRI

Volume Interpolated Breath-Hold Examination (VIBE) MRI generates images suitable for water and fat signal composition estimation. While the two-poin...

Self-Regularization with Latent Space Explanations for Controllable LLM-based Classification

Modern text classification methods heavily rely on contextual embeddings from large language models (LLMs). Compared to human-engineered features, t...

Synthetic Politics: Prevalence, Spreaders, and Emotional Reception of AI-Generated Political Images on X

Despite widespread concerns about the risks of AI-generated content (AIGC) to the integrity of social media discourse, little is known about its sca...

Precise Parameter Localization for Textual Generation in Diffusion Models

Novel diffusion models can synthesize photo-realistic images with integrated high-quality text. Surprisingly, we demonstrate through attention activ...

Use of Air Quality Sensor Network Data for Real-time Pollution-Aware POI Suggestion

This demo paper introduces AirSense-R, a privacy-preserving mobile application that delivers real-time, pollution-aware recommendations for urban po...

Effective Black-Box Multi-Faceted Attacks Breach Vision Large Language Model Guardrails

Vision Large Language Models (VLLMs) integrate visual data processing, expanding their real-world applications, but also increasing the risk of gene...

Beautiful Images, Toxic Words: Understanding and Addressing Offensive Text in Generated Images

State-of-the-art visual generation models, such as Diffusion Models (DMs) and Vision Auto-Regressive Models (VARs), produce highly realistic images....

Too Noisy To Learn: Enhancing Data Quality for Code Review Comment Generation

Code review is an important practice in software development, yet it is time-consuming and requires substantial effort. While open-source datasets h...

"I am bad": Interpreting Stealthy, Universal and Robust Audio Jailbreaks in Audio-Language Models

The rise of multimodal large language models has introduced innovative human-machine interaction paradigms but also significant challenges in machin...

Deep learning model for ECG reconstruction reveals the information content of ECG leads

This study introduces a deep learning model based on the U-net architecture to reconstruct missing leads in electrocardiograms (ECGs). The model was...

Comparison and prediction of shallow groundwater nitrate in Shaying River basin based on urban distribution using multiple machine learning approaches.

Groundwater, a pivotal water resource in numerous regions worldwide, confronts formidable challenges posed by severe nitrate pollution. Traditional re...