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

There is a need to improve communication for patients and relatives who belong to cultural minority communities in intensive care units (ICUs). As a matter of fact, language barriers negatively impact patient safety and family participation in the care of critically ill patients, as well as recruitment to clinical trials. Recent studies indicate that Google Translate and ChatGPT are not accurate enough for advanced medical terminology. Therefore, developing and implementing an ad hoc machine translation tool is essential for bridging language barriers. This tool would enable language minority communities to access advanced healthcare facilities and innovative research in a timely and effective manner, ensuring they receive the comprehensive care and information they need. Method: Key factors that facilitate access to advanced health services, in particular ICUs, for language minority communities are reviewed. Results: The existing digital communication tools in emergency departments and ICUs are reviewed. To the best of our knowledge, no AI English/French translation app has been developed for deployment in ICUs. Patient privacy and data confidentiality are other important issues that should be addressed. Conclusions: Developing an artificial intelligence-driven translation tool for intensive care units (AITIC) which uses language models trained with medical/ICU terminology datasets could offer fast and accurate real-time translation. An AITIC could support communication, and consolidate and expand original research involving language minority communities.