Public Health & Policy

Clinical Trials

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

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Jailbreaking Vision-Language Models Through the Visual Modality

The visual modality of vision-language models (VLMs) is an underexplored attack surface for bypassin...

ALEX: Automatic Language EXplanations for Interpreting Treatment Effects via Multi-Agents

Precision medicine requires understanding the underlying drivers of heterogeneous treatment response...

AERO: An AI Agent for Adaptive Eligibility Refinement and Optimization of Clinical Trial Criteria in Real-World Trial Emulation

Randomized controlled trials (RCTs) provide high internal validity but often rely on restrictive eli...

Artificial Intelligence Agents in Mental Health: A Systematic Review and Meta Analysis

The rapid rise of large language models (LLMs) and foundation models has accelerated efforts to buil...

Detecting Clinical Discrepancies in Health Coaching Agents: A Dual-Stream Memory and Reconciliation Architecture

As Large Language Model (LLM) agents transition from single-session tools to persistent systems mana...

A Sequential Multiple Assignment Randomized Trial Design with Response-Adaptive Tailoring Function

We present a novel sequential multiple assignment randomized trial (SMART) design that integrates re...

Metastasis Extraction from NSCLC Clinical Notes: A Retrospective Comparative Evaluation of Large Language Model-Based Classification

Background: Identification of metastasis status in non-small cell lung cancer (NSCLC) is a critical ...

Recipes for Calibration Checks in Safety-Critical Applications

Safety-critical prediction systems, such as autonomous vehicles, weather forecasters, and medical mo...

Edge AI for Automotive Vulnerable Road User Safety: Deployable Detection via Knowledge Distillation

Deploying accurate object detection for Vulnerable Road User (VRU) safety on edge hardware requires ...

One Perturbation, Two Failure Modes: Probing VLM Safety via Embedding-Guided Typographic Perturbations

Typographic prompt injection exploits vision language models' (VLMs) ability to read text rendered i...

TrialCalibre: A Fully Automated Causal Engine for RCT Benchmarking and Observational Trial Calibration

Real-world evidence (RWE) studies that emulate target trials increasingly inform regulatory and clin...

BETA: Resting-state fMRI Biotypes for tDCS Efficacy in Anxiety Among Older Adults At Risk For Alzheimer's Disease

Anxiety is usually gauged by self-report, yet a single symptom level can reflect disparate neural ci...

Does Machine Unlearning Preserve Clinical Safety? A Risk Analysis for Medical Image Classification

The application of Deep Learning in medical diagnosis must balance patient safety with compliance wi...

Risk-Aware Robust Learning: Reducing Clinical Risk under Label Noise in Medical Image Classification

Noisy labels are a pervasive challenge in medical image classification, where annotation errors aris...

Sum-of-Checks: Structured Reasoning for Surgical Safety with Large Vision-Language Models

Purpose: Accurate assessment of the Critical View of Safety (CVS) during laparoscopic cholecystectom...

MedSafe-Dx (v0): A Safety-Focused Benchmark for Evaluating LLMs in Clinical Diagnostic Decision Support

MedSafe-Dx (v0), introduces a new safety-focused benchmark for evaluating large language models in c...

Dissecting clinical reasoning failures in frontier artificial intelligence using 10,000 synthetic cases

Background: Current medical large language model (LLM) evaluations largely rely on small collections...

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