Boston-based athenahealth introduced an AI-native clinical encounter that uses ambient and generative artificial intelligence to streamline documentation, decision-making and orders during the patient ...

Companies this past month announced many new products and services that use artificial intelligence to automate complex processes, secure data and improve care coordination and interoperability ...

Abstract: Named entity recognition (NER) in electronic medical records (EMRs) is critical for identifying medical entities, constructing medical knowledge graphs, and supporting clinical ...

GLSydney Institute for Infectious Diseases, The University of Sydney, Sydney, NSW, Australia GMDepartment of Infectious Diseases, Sydney Children's Hospital, Randwick, NSW, Australia ...

Abstract: Feature sparse problem is commonly existing in patient similarity calculation task with clinical data, to track which, some approaches have been proposed to use Graph Neural Network (GNN) to ...

Doctors often must make critical decisions in minutes, relying on incomplete information. While electronic health records contain vast amounts of patient data, much of it remains difficult to ...

What is the best BF6 M39 EMR loadout? The DMR class of weapon fills a very specific niche, and sometimes it can seem like they're stuck somewhere in between a carbine and a sniper rifle. Not capable ...

Boeing recently sent a newly serviced 737 main battery to Southwest Airlines with an electronic airworthiness approval tag, kicking off a program that those involved hope will grow quickly and ...

Background: Currently, perioperative stakeholders are guided to provide general anesthesia (GA) patients with either two or four antiemetic prophylaxis (AEPPx) medications based on the 1990s legacy ...

Efforts to achieve polio eradication in the Eastern Mediterranean Region (EMR) are confronted by several barriers stemming from the volatile security and political instability in several countries, to ...