AI Detects Medication Errors

This is a anesthesia news story, published by ScienceDaily, that relates primarily to Justin Chan news.

anesthesia news

For more anesthesia news, you can click here:

more anesthesia news

Justin Chan news

For more Justin Chan news, you can click here:

more Justin Chan news

medical innovations news

For more medical innovations news, you can click here:

more medical innovations news

ScienceDaily news

For more news from ScienceDaily, you can click here:

more news from ScienceDaily

About the Otherweb

Otherweb, Inc is a public benefit corporation, dedicated to improving the quality of news people consume. We are non-partisan, junk-free, and ad-free. We use artificial intelligence (AI) to remove junk from your news feed, and allow you to select the best health news, business news, entertainment news, and much more. If you like medical innovations news, you might also like this article about

clinical medication errors

. We are dedicated to bringing you the highest-quality news, junk-free and ad-free, about your favorite topics. Please come every day to read the latest Wearable cameras news, first wearable camera system news, medical innovations news, and other high-quality news about any topic that interests you. We are working hard to create the best news aggregator on the web, and to put you in control of your news feed - whether you choose to read the latest news through our website, our news app, or our daily newsletter - all free!

medication errors

ScienceDaily

•

Wearable cameras allow AI to detect medication errors

Summary

Nutrition label

80% Informative

System could become a critical safeguard, especially in operating rooms, intensive-care units and emergency-medicine settings.

System does not directly read the wording on each vial, but scans for other visual cues: vial and syringe size and shape, vial cap color, label print size.

Drug administration errors are the most frequently reported critical incidents in anesthesia .

Note: Content may be edited for style and length. Journal Reference: - Justin Chan , Solomon Nsumba , Mitchell Wortsman , Achal Dave , Ludwig Schmidt , Shyamnath Gollakota , Kelly Michaelsen . Detecting clinical medication errors with AI enabled wearable cameras. npj Digital Medicine , 2024 ; 7 ( 1 ) DOI: 10.1038 /s41746-024-01295-2 Cite This Page:.