Clinical Trials

Reinforcement Learning for Chronic Care Pathway Optimization: A Unified Framework across Three Clinical Goal Types

Objective: Chronic care requires sequential treatment under competing biomarker, safety, and cost constraints, yet clinical goal structures differ across diseases. We asked whether one physiology-informed reinforcement learning (RL) paradigm adapts to heterogeneous chronic-care goals without disease-specific policy architectures. Materials and Methods: We formalized a Type A/B/C clinical goal taxo...

VLM-CASE: Vision-Language Model Enabled Context-Adaptive Safety Envelopes for Anticipatory Safe Autonomous Driving

Adverse driving conditions, such as bad weather, remain a principal barrier to autonomous driving because they degrade two things at once: what the vehicle can perceive and what it can physically do. Human drivers cope by anticipation, reasoning about the scene and re-budgeting speed, following distance, and steering before grip or sight is lost, whereas current autonomous driving systems at best ...

Transplanting, inverting, and preventing a misalignment persona: method-conditional emergent misalignment in Qwen2.5

Emergent misalignment (EM) -- the broad misbehaviour a language model acquires after fine-tuning on narrow harmful data -- is mediated in Qwen2.5 mode...

Benchmarking large language models for ACMG/AMP variant interpretation and variant calling

Agentic large language models are increasingly used across the genomic workflow, from variant calling to clinical interpretation, yet they are evaluat...

Deep Learning based Quantification of Root Exposure in Lower Anterior Teeth using Intraoral camera image

This study compared and evaluated two widely used deep learning-based artificial intelligence (AI) models, U-Net++ and YOLOv11, for quantifying tooth ...

ART for Diffusion Sampling: Continuous-Time Control and Actor-Critic Learning

We study timestep allocation for score-based diffusion sampling, where a learned reverse-time dynamics is discretized on a finite grid. Uniform and ha...

Multi-modal Rail Crossing Safety Analysis

Given one or more images of a railway crossing, can we leverage visual cues that allow us to robustly estimate how safe it is? Can we improve our abil...

Evaluating Open-Source Wrist-Worn Accelerometer Models for Sedentary Time Detection Against Thigh-Worn Accelerometer Data

Abstract Objective Wrist-worn accelerometers are common in large-scale epidemiological studies, but their ability to measure sedentary behaviour in fr...

Autonomous generation of decision-grade clinical evidence

Medical practice is bottlenecked by the slow production of high-quality clinical evidence. Despite progress in automating selected stages, autonomous ...

Harnessing Textual Refusal Directions for Multimodal Safety

To improve safety in Large Language Models (LLMs) we can either perform post-training alignment or exploit refusal directions in the activation space....

Proposed Context-of-Use Evaluation Framework for Medication Management Tasks Completed by Generative Artificial Intelligence

Background: Standardized evaluation of agentic artificial intelligence (AI) for medication management is lacking. Given the potential lethality of med...

LLM-based Multimodal Personality Recognition via Facial Action Unit-Text Semantic Fusion

Personality recognition in asynchronous video interviews (AVIs) has become increasingly important due to their widespread adoption in modern recruitme...

Bridging the Gap Between Image Restoration and Navigational Safety in Hazy Conditions: A New Visibility Estimation Metric for Maritime Surveillance

Visibility distance is critical to maritime navigational safety because it determines the effective observation range of shipborne and shore-based mon...

CaresAI at CT-DEB26: Detecting Dosing Errors In Clinical Trials Using Domain-Specific Transformer Embeddings and Classification Models

Medication errors, particularly dosing errors in clinical trials (CT), can lead to patient harm, adverse drug events and worse patient outcomes. Dosin...

Desktop-Scale Hit-Point Discovery for Intrinsically Disordered α-Synuclein Using State-Space Compression and a Discrete Phase-Interference Search Operator

The accessible chemical space dwarfs any tractable screening budget, and most artificial intelligence drug discovery pipelines respond by docking and ...

Halt Fast! Early Stopping for Certified Robustness

Randomized Smoothing (RS) provides rigorous robustness guarantees for neural networks without architectural constraints, yet its adoption is limited b...

Long-term memory performance optimization via Neural network-based curve fitting in Drosophila

Long-term memory (LTM) formation typically requires extensive training. While operant conditioning is expected to produce stronger LTM than classical ...

The Inattentional Gap: Task-Conditioned Language and Vision Models Omit the Safety-Critical Signals They Can Otherwise Report

AI safety is evaluated by how reliably a model detects the hazards it is told to find, yet accidents often arise from the hazard no one specified. We ...

Generative AI avatar videos for tobacco prevention on social media: a randomized controlled trial

Short-form video platforms increasingly shape how young audiences encounter health information. Generative artificial intelligence can produce standar...

Self-administered computerized cognitive training for cognitive deficits in individuals with metabolic syndrome: a randomized controlled trial

Background: Metabolic syndrome (MetS) has been associated with cognitive decline. Considering its increasing prevalence worldwide, the goal of this st...