Revolutionizing Acute Stroke Care: A Review of Food and Drug Administration-Approved Software as Medical Devices for Stroke Triage.

Stroke remains a critical global health challenge, with ischemic stroke comprising most cases and necessitating rapid, effective treatment to improve patient outcomes. This review explores the integration of artificial intelligence (AI) and machine learning into medical devices for stroke triaging, highlighting their impact on reducing notification times, latency in care, and health disparities. By analyzing Food and Drug Administration-approved AI-enabled devices under the "Radiological computer-assisted triage and notification software" regulation category, we assess their sensitivity, specificity, and time-to-notification as the measure of their overall effectiveness in clinical settings.

On the Versatility of the -, -, and -Hybridized Chalcogen-Bearing Molecules To Engage in Type I Chalcogen···Chalcogen Interactions: A Quantum Mechanical Investigation of Like···Like and Unlike Complexes.

The predilection of -, -, and -hybridized chalcogen-bearing molecules to engage in type I chalcogen···chalcogen interactions was comparatively unveiled in like···like/unlike CY···YC, YCY···YCY, and FY···YF (where Y = O, S, and Se) complexes, respectively. Upon the optimized monomers, a potential energy surface (PES) scan was conducted to pinpoint the most favorable complexes. The energetic findings unveiled the ability of the investigated systems to engage in the interactions under study with binding energy values ranging from -0.

Supervised learning-based artificial senses for non-destructive fish quality classification.

Human sensory techniques are inadequate for automating fish quality monitoring and maintaining controlled storage conditions throughout the supply chain. The dynamic monitoring of a single quality index cannot anticipate explicit freshness losses, which remarkably drops consumer acceptability. For the first time, a complete artificial sensory system is designed for the early detection of fish quality prediction.