Editorial
The topic of artificial intelligence (AI) makes headlines almost daily. Eliminating any fatalistic doomsday scenarios, current literature is raising interesting points around the useability of AI and the ethical considerations regular users of AI should not ignore. In the healthcare space, the number one question seems to be, Is it…
Harnessing power of AI: Operational improvements for the OR
ORs are at the heart of healthcare organizations, where critical decisions are made, often under immense pressure. This pressure has escalated with ever-increasing demands, growing complexities, and the constant requirement for innovative solutions. In today’s rapidly evolving technological landscape, artificial intelligence (AI), machine learning (ML), and the emerging generative AI…
Discrepancies in FDA clearance, marketing of AI-, ML-enabled medical devices
Editor's Note This study from New York University and NYU Langone Health, New York City, finds discrepancies between the marketing and 510(k) clearance of artificial intelligence (AI)- or machine learning (ML)-enabled medical devices, with some devices being marketed as having capabilities not approved by the Food and Drug Administration (FDA).…
Effectiveness of AI in detecting hip fractures, predicting postop outcomes
Editor's Note This Canadian meta-analysis finds that artificial intelligence (AI) has the potential to automate hip fracture diagnoses; however, complicated models may not provide benefit over traditional patient-specific postoperative outcomes predictions. Of 39 studies included in the analysis, 18 used AI models to diagnose hip fractures on plain radiographs and…
AI may improve colonoscopy accuracy
Editor's Note Researchers at Mayo Clinic Healthcare in London are investigating how artificial intelligence (AI) can be used to identify colon polyps that might otherwise get overlooked during colonoscopy. The AI system works alongside the physician in real time, scanning the colonoscopy video feed and drawing small, red boxes around…
INDUSTRY SPOTLIGHT: LeanTaaS
Download the PDF Version of the Industry Spotlight In 2013, LeanTaaS partnered with Stanford Health Care to solve an infusion scheduling challenge and created an algorithm to optimally match available supply with ongoing demand. The solution for Stanford worked, leading to 18 months of refining algorithms before creating the product,…
The superior efficacy of machine learning based AI tools
With all the factors involved in optimizing OR utilization, assigning OR slots is a complex proposition. When you consider that the average cost to run a fully equipped OR is now at approximately $1,000 per hour in staff and equipment costs, it is more important than ever for hospitals to…
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