Abstract

The surge in artificial intelligence (AI) prompts a reassessment of linguistic validation methods for patient-reported outcome (PRO) measures. The robust linguistic process, designed to adapt PRO measures for different cultures and languages, is upheld by regulators and the outcomes research community for its value in maintaining concept equivalence across global trial data. Its methods are entrenched in human translation and review, making it more challenging to integrate AI (machine learning, deep learning, natural language processing) compared to other parts of the global localisation industry. This article provides an overview of the key challenges in integrating linguistic validation and AI. Despite these hurdles, it advocates for the industry to embrace the potential benefits through collaborative and responsible innovation.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.