Public Health & Policy

Clinical Trials

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

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Artificial intelligence and machine learning in ocular oncology, retinoblastoma (ArMOR).

PURPOSE: To test the accuracy of a trained artificial intelligence and machine learning (AI/ML) mode...

May 2025 40272303
Optimizing Treatment: The Role of Pharmacology, Genomics, and AI in Improving Patient Outcomes.

Recent advances in pharmacology are revolutionizing drug discovery and treatment strategies through ...

May 2025 40285487
Real-Time AI-Assisted Insulin Titration System for Glucose Control in Patients With Type 2 Diabetes: A Randomized Clinical Trial.

IMPORTANCE: Type 2 diabetes (T2D) is one of the most prevalent chronic diseases in the world. Insuli...

May 2025 40332936
Who Gets the Callback? Generative AI and Gender Bias

Generative artificial intelligence (AI), particularly large language models (LLMs), is being rapid...

LLM Agent Swarm for Hypothesis-Driven Drug Discovery

Drug discovery remains a formidable challenge: more than 90 percent of candidate molecules fail in...

Assessing Surrogate Heterogeneity in Real World Data Using Meta-Learners

Surrogate markers are most commonly studied within the context of randomized clinical trials. Howe...

Are Vision LLMs Road-Ready? A Comprehensive Benchmark for Safety-Critical Driving Video Understanding

Vision Large Language Models (VLLMs) have demonstrated impressive capabilities in general visual t...

Towards NSFW-Free Text-to-Image Generation via Safety-Constraint Direct Preference Optimization

Ensuring the safety of generated content remains a fundamental challenge for Text-to-Image (T2I) g...

Safety Monitoring for Learning-Enabled Cyber-Physical Systems in Out-of-Distribution Scenarios

The safety of learning-enabled cyber-physical systems is compromised by the well-known vulnerabili...

Safe Physics-Informed Machine Learning for Dynamics and Control

This tutorial paper focuses on safe physics-informed machine learning in the context of dynamics a...

VLMGuard-R1: Proactive Safety Alignment for VLMs via Reasoning-Driven Prompt Optimization

Aligning Vision-Language Models (VLMs) with safety standards is essential to mitigate risks arisin...

Interpretable AI-driven Guidelines for Type 2 Diabetes Treatment from Observational Data

Objective: Create precise, structured, data-backed guidelines for type 2 diabetes treatment progre...

Accountable Liveness

Safety and liveness are the two classical security properties of consensus protocols. Recent works...

Safety with Agency: Human-Centered Safety Filter with Application to AI-Assisted Motorsports

We propose a human-centered safety filter (HCSF) for shared autonomy that significantly enhances s...

Recommending Clinical Trials for Online Patient Cases using Artificial Intelligence

Clinical trials are crucial for assessing new treatments; however, recruitment challenges - such a...

LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models

Recent advancements in Large Language Models (LLMs) have enabled them to approach human-level pers...

Do We Really Need Curated Malicious Data for Safety Alignment in Multi-modal Large Language Models?

Multi-modal large language models (MLLMs) have made significant progress, yet their safety alignme...

The Structural Safety Generalization Problem

LLM jailbreaks are a widespread safety challenge. Given this problem has not yet been tractable, w...

Dose-finding design based on level set estimation in phase I cancer clinical trials

The primary objective of phase I cancer clinical trials is to evaluate the safety of a new experim...

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