Clinical Trials

Legal Implication in Utilizing Automated Robots: A Written Informed Consent Form Proposal.

BACKGROUND: Robotic systems enhance physicians' capabilities by replicating hand movements in real-time, ensuring precise control and a quick return to conventional procedures if patient safety is compromised. Physicians performing robot-assisted procedures bear ultimate responsibility, sharing potential liability with manufacturers for malfunctions.

A Machine Learning Approach for Investigating Variable Importance in Relationship and Sexual Satisfaction: The Role of Interpersonal Mindfulness and Psychological Safety.

Numerous studies have shown that mindfulness is positively associated with relationship and sexual satisfaction. However, most have examined the benefits of intrapersonal or trait mindfulness, rather than directly investigating interpersonal mindfulness or considering polyvagal theory. Our main objective was to determine the variable importance of interpersonal mindfulness and psychological safety...

Publisher Correction: GPT-4 assistance for improvement of physician performance on patient care tasks: a randomized controlled trial.

Predicting Targeted Therapy Resistance in Non-Small Cell Lung Cancer Using Multimodal Machine Learning

Lung cancer is the primary cause of cancer death globally, with non-small cell lung cancer (NSCLC) emerging as its most prevalent subtype. Among NSC...

Reinforcement Learning for Safe Autonomous Two Device Navigation of Cerebral Vessels in Mechanical Thrombectomy

Purpose: Autonomous systems in mechanical thrombectomy (MT) hold promise for reducing procedure times, minimizing radiation exposure, and enhancing ...

RECALL-MM: A Multimodal Dataset of Consumer Product Recalls for Risk Analysis using Computational Methods and Large Language Models

Product recalls provide valuable insights into potential risks and hazards within the engineering design process, yet their full potential remains u...

An Efficient Training Algorithm for Models with Block-wise Sparsity

Large-scale machine learning (ML) models are increasingly being used in critical domains like education, lending, recruitment, healthcare, criminal ...

GateLens: A Reasoning-Enhanced LLM Agent for Automotive Software Release Analytics

Ensuring the reliability and effectiveness of software release decisions is critical, particularly in safety-critical domains like automotive system...

ShieldAgent: Shielding Agents via Verifiable Safety Policy Reasoning

Autonomous agents powered by foundation models have seen widespread adoption across various real-world applications. However, they remain highly vul...

Playing the Fool: Jailbreaking LLMs and Multimodal LLMs with Out-of-Distribution Strategy

Despite the remarkable versatility of Large Language Models (LLMs) and Multimodal LLMs (MLLMs) to generalize across both language and vision tasks, ...

The Role of Computational Modeling in Enhancing Thermal Safety During Cardiac Ablation

Objective: In this review, we aim to provide an analysis of current cardiac ablation techniques, such as radiofrequency ablation (RF), cryoablation,...

Identifying responders to gabapentin for the treatment of alcohol use disorder: an exploratory machine learning approach.

BACKGROUND: Gabapentin, an anticonvulsant medication, has been proposed as a treatment for alcohol use disorder (AUD). A multisite study tested gabape...

MIRAGE: Multimodal Immersive Reasoning and Guided Exploration for Red-Team Jailbreak Attacks

While safety mechanisms have significantly progressed in filtering harmful text inputs, MLLMs remain vulnerable to multimodal jailbreaks that exploi...

Boosting Resolution Generalization of Diffusion Transformers with Randomized Positional Encodings

Resolution generalization in image generation tasks enables the production of higher-resolution images with lower training resolution overhead. Howe...

AgentSpec: Customizable Runtime Enforcement for Safe and Reliable LLM Agents

Agents built on LLMs are increasingly deployed across diverse domains, automating complex decision-making and task execution. However, their autonom...

Quantile-Based Randomized Kaczmarz for Corrupted Tensor Linear Systems

The reconstruction of tensor-valued signals from corrupted measurements, known as tensor regression, has become essential in many multi-modal applic...

Reason2Attack: Jailbreaking Text-to-Image Models via LLM Reasoning

Text-to-Image(T2I) models typically deploy safety filters to prevent the generation of sensitive images. Unfortunately, recent jailbreaking attack m...

Unraveling Pedestrian Fatality Patterns: A Comparative Study with Explainable AI

Road fatalities pose significant public safety and health challenges worldwide, with pedestrians being particularly vulnerable in vehicle-pedestrian...

Random-sketching Techniques to Enhance the Numerical Stability of Block Orthogonalization Algorithms for s-step GMRES

We integrate random sketching techniques into block orthogonalization schemes needed for s-step GMRES. The resulting block orthogonalization schemes...

Truthful Elicitation of Imprecise Forecasts

The quality of probabilistic forecasts is crucial for decision-making under uncertainty. While proper scoring rules incentivize truthful reporting o...