3 articles tagged with #remote-monitoring. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.
Researchers developed Sentinel, an autonomous AI agent that achieves 95.8% emergency sensitivity in clinical triage for remote patient monitoring, outperforming individual clinicians while costing only $0.34 per triage. The AI system addresses the core scalability issues that caused previous remote monitoring trials to fail due to data overload.
Researchers developed QoR-compact, a five-question alternative to the 15-item Quality of Recovery survey for remote patient monitoring, achieving statistically comparable predictive accuracy (AUC-ROC 0.968) while reducing patient burden by two-thirds. The streamlined tool addresses low compliance rates in daily post-surgical assessments while maintaining clinical reliability for predicting recovery outcomes.
Researchers developed Quantitative Movement Testing (QMT), a computer vision system that measures patient movement from smartphone videos with clinical-grade accuracy. The technology uses deep learning-based 3D pose estimation to extract kinematic biomarkers, validated against optical motion capture in lab settings and tested in real-world chronic pain studies.
