Public Health & Policy

Clinical Trials

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

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STRAP-ViT: Segregated Tokens with Randomized -- Transformations for Defense against Adversarial Patches in ViTs

Adversarial patches are physically realizable localized noise, which are able to hijack Vision Trans...

HomeSafe-Bench: Evaluating Vision-Language Models on Unsafe Action Detection for Embodied Agents in Household Scenarios

The rapid evolution of embodied agents has accelerated the deployment of household robots in real-wo...

AI is Smart. Is it Wise? Quantifying the Effect of Patient-Choice (β) on Physical Outcomes

Large language models (LLMs) increasingly guide clinical decisions through population-level evidence...

HomeSafe-Bench: Evaluating Vision-Language Models on Unsafe Action Detection for Embodied Agents in Household Scenarios

The rapid evolution of embodied agents has accelerated the deployment of household robots in real-wo...

Ensuring Safety in Automated Mechanical Ventilation through Offline Reinforcement Learning and Digital Twin Verification

Mechanical ventilation (MV) is a life-saving intervention for patients with acute respiratory failur...

A prospective clinical feasibility study of a conversational diagnostic AI in an ambulatory primary care clinic

Large language model (LLM)-based AI systems have shown promise for patient-facing diagnostic and man...

Semantic Risk Scoring of Aggregated Metrics: An AI-Driven Approach for Healthcare Data Governance

Large healthcare institutions typically operate multiple business intelligence (BI) teams segmented ...

A prospective clinical feasibility study of a conversational diagnostic AI in an ambulatory primary care clinic

Large language model (LLM)-based AI systems have shown promise for patient-facing diagnostic and man...

Visual Self-Fulfilling Alignment: Shaping Safety-Oriented Personas via Threat-Related Images

Multimodal large language models (MLLMs) face safety misalignment, where visual inputs enable harmfu...

OD-RASE: Ontology-Driven Risk Assessment and Safety Enhancement for Autonomous Driving

Although autonomous driving systems demonstrate high perception performance, they still face limitat...

Red-Teaming Medical AI: Systematic Adversarial Evaluation of LLM Safety Guardrails in Clinical Contexts

Background: Large language models (LLMs) are increasingly deployed in medical contexts as patient-fa...

Slice-wise quality assessment of high b-value breast DWI via deep learning-based artifact detection

Diffusion-weighted imaging (DWI) can support lesion detection and characterization in breast magneti...

MUSE: A Run-Centric Platform for Multimodal Unified Safety Evaluation of Large Language Models

Safety evaluation and red-teaming of large language models remain predominantly text-centric, and ex...

An Empirical Analysis of Calibration and Selective Prediction in Multimodal Clinical Condition Classification

As artificial intelligence systems move toward clinical deployment, ensuring reliable prediction beh...

COOL-MC: Verifying and Explaining RL Policies for Platelet Inventory Management

Platelets expire within five days. Blood banks face uncertain daily demand and must balance ordering...

Temporal dynamics of radiotherapy and chemotherapy response in lower-grade gliomas using causal machine learning

Lower-grade gliomas (World Health Organization [WHO] grades 2-3) exhibit variable treatment response...

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