Artificial Intelligence-Driven Translation Tools in Intensive Care Units for Enhancing Communication and Research

Area of Science:

• Medical Informatics
• Health Communication
• Artificial Intelligence in Healthcare

Background:

• Language barriers in intensive care units (ICUs) hinder patient safety, family engagement, and clinical trial participation for cultural minority communities.
• Current tools like Google Translate and ChatGPT lack the accuracy needed for complex medical terminology.

Purpose of the Study:

• To address the critical need for improved communication in ICUs for language minority patients and their families.
• To explore the development of a specialized machine translation tool to bridge healthcare language gaps.

Main Methods:

• Review of key factors enabling access to advanced health services, specifically ICUs, for language minority populations.
• Assessment of existing digital communication tools within emergency departments and ICUs.

Main Results:

• Current digital communication tools are insufficient for the specific needs of ICUs.
• No AI-powered English/French translation application is currently available for ICU deployment.
• Patient privacy and data confidentiality are significant considerations for any new tool.

Conclusions:

• An artificial intelligence-driven translation tool for intensive care units (AITIC), trained on medical/ICU datasets, can provide accurate, real-time translation.
• AITIC can enhance communication and support research involving language minority communities in critical care settings.