Public Health & Policy

Clinical Trials

Latest AI and machine learning research in clinical trials for healthcare professionals.

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Physics-Informed Autoencoder for Prostate Tissue Microstructure Profiling with Hybrid Multidimensional MRI.

Purpose To evaluate the performance of Physics-Informed Autoencoder (PIA), a self-supervised deep le...

Mar 2025 39907585
COVID-19 Patients Benefitting From Remdesivir for Improved Survival: A Neural Network-Based Approach.

Conflicting results from randomized trials regarding the efficacy of remdesivir for COVID-19 have be...

Mar 2025 40059457
SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models

Traditional autonomous driving systems often struggle to integrate high-level reasoning with low-l...

Learning Vision-Based Neural Network Controllers with Semi-Probabilistic Safety Guarantees

Ensuring safety in autonomous systems with vision-based control remains a critical challenge due t...

Generating patient cohorts from electronic health records using two-step retrieval-augmented text-to-SQL generation

Clinical cohort definition is crucial for patient recruitment and observational studies, yet trans...

Beware of Your Po! Measuring and Mitigating AI Safety Risks in Role-Play Fine-Tuning of LLMs

Role-playing enables large language models (LLMs) to engage users in immersive and personalized in...

Medical Hallucinations in Foundation Models and Their Impact on Healthcare

Foundation Models that are capable of processing and generating multi-modal data have transformed ...

3D Nephrographic Image Synthesis in CT Urography with the Diffusion Model and Swin Transformer

Purpose: This study aims to develop and validate a method for synthesizing 3D nephrographic phase ...

Repurposing the scientific literature with vision-language models

Leading vision-language models (VLMs) are trained on general Internet content, overlooking scienti...

Adaptive Shielding via Parametric Safety Proofs

A major challenge to deploying cyber-physical systems with learning-enabled controllers is to ensu...

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

Large Vision-Language Models (LVLMs) have made significant strides in multimodal comprehension, th...

Enhancing Hepatopathy Clinical Trial Efficiency: A Secure, Large Language Model-Powered Pre-Screening Pipeline

Background: Recruitment for cohorts involving complex liver diseases, such as hepatocellular carci...

A Systematic Review of Open Datasets Used in Text-to-Image (T2I) Gen AI Model Safety

Novel research aimed at text-to-image (T2I) generative AI safety often relies on publicly availabl...

CurricuVLM: Towards Safe Autonomous Driving via Personalized Safety-Critical Curriculum Learning with Vision-Language Models

Ensuring safety in autonomous driving systems remains a critical challenge, particularly in handli...

ThinkGuard: Deliberative Slow Thinking Leads to Cautious Guardrails

Ensuring the safety of large language models (LLMs) is critical as they are deployed in real-world...

Investigating the Impact of Quantization Methods on the Safety and Reliability of Large Language Models

Large Language Models (LLMs) have emerged as powerful tools for addressing modern challenges and e...

SATA: Safe and Adaptive Torque-Based Locomotion Policies Inspired by Animal Learning

Despite recent advances in learning-based controllers for legged robots, deployments in human-cent...

SEA: Low-Resource Safety Alignment for Multimodal Large Language Models via Synthetic Embeddings

Multimodal Large Language Models (MLLMs) have serious security vulnerabilities.While safety alignm...

LLM Safety for Children

This paper analyzes the safety of Large Language Models (LLMs) in interactions with children below...

SafeEraser: Enhancing Safety in Multimodal Large Language Models through Multimodal Machine Unlearning

As Multimodal Large Language Models (MLLMs) develop, their potential security issues have become i...

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