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Patient safety / Risk Management

Latest AI and machine learning research in patient safety / risk management for healthcare professionals.

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Reflection-Guided Dynamics Rectification for Text-to-Image Generation

Fine-grained rectification of existing generations under a limited additional budget remains a key p...

ExpertTwins: Auditable Long Horizon Scientific Panels through Grounded Expertise

Multi-agent language-model systems increasingly assign roles to agents and let them deliberate. A ro...

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Unmentioned Checklist Findings Change How Reinforcement Learning Appears to Improve Chest Radiograph Report Checking

Automated checks of radiology reports may rely on AI-generated checklists that leave findings unment...

The Poisoned Conversation: Privacy-Leaking Watermarks in Unified Multimodal Models

Multimodal models are increasingly shifting toward unified architectures that understand and generat...

When the Cross-Silo Federation Goes Offline: Continual Learning for Site Onboarding with Limited Unlabeled Data

An organization often holds too little labeled data to train a model that generalizes, and the recor...

Scoring Higher, Answering Worse: Mitigating Reward Hacking in Rubric-Based RL via Protocol-Level Rubrics

Rubric-based reinforcement learning (Rubric-RL) trains language models where no verifier exists. A j...

Where Privacy Belongs: Placement Diagnosis and Certified Selection for Private Counterfactual Explanations on Graphs

Counterfactual explanations for graph neural networks (GNNs) find the minimal intervention that flip...

PanVasc Research for AI assisted evidence analysis in panvascular intervention

Panvascular intervention research requires evidence workflows that preserve source identity, outcome...

From Offline Proxies to Online Decisions: A Layered Engagement Evaluation Framework for Conversational AI

Online A/B experiments are the decision standard for user engagement, but traffic and readout time l...

Multi-center Medical Data Mining with FL-Net - A One-stop Shop for Federated Learning

Federated learning enables collaborative training without sharing patient-level data, but most studi...

Predicting Privacy Leakage from Weight Spectral Density

Membership inference attacks (MIAs) are widely used to audit the privacy disclosure risk of machine ...

Untangling the Mechanisms of Misleading Context in Medical Question Answering

Large language models now answer medical questions with expert-level performance. However, the conte...

CHARMS and PROBAST+AI: an updated template for Data Extraction and Risk of Bias Assessment in systematic reviews of prediction models

Background: Systematic reviews of clinical prediction models increasingly include studies using arti...

Prospective In-silico Simulation of the VESALIUS-CV Trial Using Biomedical Knowledge Graph and Real-World Data-Driven AI Modeling

Background. Cardiovascular-outcomes trials are lengthy, costly, and associated with substantial unce...

ARISMA: Guidelines for AI- and LLM-Assisted Systematic Reviews, Scoping Reviews, and Mapping Studies

Systematic reviews, scoping reviews, mapping studies, and related evidence syntheses are increasingl...

EviRank: Structured Relevance Evidence for Multimodal Image Re-ranking

Real-world image search queries are multimodal and compositional: ``find this shirt in pink'' specif...

G-CARL: Grounded Checklist-Aligned Reward Learning for Patient-Oriented Medical Report Interpretation

Personalized interpretation of medical reports has emerged as an increasingly important need among p...

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