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Mapping Aneurysm Risk with AI-Powered Blood Flow

11.12.2025 by qfx

The study demonstrates that blood viscosity, when modeled with a modified Casson model, exhibits shear-rate dependency-varying dynamically across physiological shear rates found in brain aneurysm hemodynamics-a departure from the simplification of constant viscosity assumed by the common Newtonian model with $μ = 4$ mPa⋅s.

A new approach leverages graph neural networks to dramatically accelerate the simulation of blood flow within intracranial aneurysms, paving the way for faster, more accurate risk assessment.

Categories Science

When the Experts Log Off: The Stack Exchange Strike and Its Discontents

11.12.2025 by qfx

A recent community strike on Stack Exchange highlights the growing tensions between platform policies, AI integration, and the rights of volunteer contributors.

Categories Science

Tracking Disparities: How AI Mirrors Healthcare’s Evolving Focus

11.12.2025 by qfx

A new analysis reveals how large language models are reflecting-and potentially shaping-research trends in understanding and addressing healthcare inequities.

Categories Science

Turning Accidents into Insights: A New Approach to AV Safety Testing

10.12.2025 by qfx

The system generates dynamically plausible and controllable risky states by integrating a motion predictor with a variational autoencoder’s latent representation and optimizing within that latent space-a process destined to become tomorrow’s technical debt as production scenarios inevitably expose unforeseen limitations.

Researchers are leveraging real-world crash data to create realistic and controllable scenarios for rigorously testing the safety of autonomous vehicles.

Categories Science

Sizing Up AI: Predicting GPU Memory Needs for Multimodal Models

10.12.2025 by qfx

Training increasingly complex AI models requires careful management of GPU resources, and accurately forecasting memory usage is now critical for efficient development.

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Mapping Risk: A New AI Approach to Predicting Sudden Death and Stroke

10.12.2025 by qfx

The proposed Geometric-Stochastic Multimodal Deep Learning (GSM-DL) framework establishes a system architecture designed to integrate geometric and stochastic approaches within a deep learning paradigm.

Researchers have developed a novel artificial intelligence framework that combines geometric and stochastic modeling of physiological data to improve prediction of life-threatening events like SUDEP and stroke.

Categories Science

Simulating Economic Shocks with AI

10.12.2025 by qfx

A scenario generation pipeline leverages large language models and information retrieval to produce structured economic forecasts-encompassing GDP, inflation, and interest rates-subject to both hard and soft plausibility constraints, then translates these forecasts into asset return projections via volatility scaling, linear principal component analysis, and a nonlinear polynomial factor incorporating textual amplification, with regime severity modulated by a mixing parameter $λ$ and performance benchmarked against deterministic baselines.

Researchers are leveraging the power of large language models to generate realistic, data-driven stress tests for financial portfolios.

Categories Science

Gridlock Avoided: Simulating Power Grid Resilience Under Stress

10.12.2025 by qfx

The study leverages a topological representation to analyze the IEEE 118-bus test system, providing a framework for understanding its interconnected network structure and facilitating rigorous analysis of power flow dynamics.

A new methodology leverages high-performance computing to comprehensively assess power grid vulnerability to cascading failures and identify critical infrastructure.

Categories Science

Quantifying the AI Threat Landscape

10.12.2025 by qfx

Quantitative risk modeling offers a demonstrable advantage by translating uncertain future events into probabilistic outcomes, thereby enabling proactive mitigation strategies and informed decision-making under conditions of inherent financial exposure, ultimately shifting the focus from reactive crisis management to preemptive resource allocation based on calculated probabilities-a transformation crucial for sustainable portfolio health.

A new methodology moves beyond qualitative assessments to model cybersecurity risks amplified by artificial intelligence.

Categories Science

Small Models, Big Insights: Predicting Crash Injuries with Limited Resources

10.12.2025 by qfx

The XGBoost model elucidates injury severity prediction through feature impact analysis, demonstrating how individual event characteristics-ranging from low (blue) to high (red) values-systematically shift the predicted outcome, effectively mapping the influence of each variable on the model’s assessment.

A new pipeline leverages the efficiency of small language models alongside traditional tree ensembles to accurately predict injury severity from city-wide crash data.

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