Desiderata for delivering NLP to accelerate healthcare AI advancement and a Mayo Clinic NLP-as-a-service implementation

• Published in: NPJ digital medicine Vol. 2; no. 1; p. 130
• Main Authors: Wen, Andrew, Fu, Sunyang, Moon, Sungrim, El Wazir, Mohamed, Rosenbaum, Andrew, Kaggal, Vinod C., Liu, Sijia, Sohn, Sunghwan, Liu, Hongfang, Fan, Jungwei
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 17-12-2019; Nature Publishing Group
• Subjects: 692/308; 692/700; Artificial intelligence; Biomedicine; Biotechnology; Digital technology; Health informatics; Medicine; Medicine & Public Health; Perspective; Health care; Medical research
• ISSN: 2398-6352; 2398-6352
• DOI: 10.1038/s41746-019-0208-8

Data is foundational to high-quality artificial intelligence (AI). Given that a substantial amount of clinically relevant information is embedded in unstructured data, natural language processing (NLP) plays an essential role in extracting valuable information that can benefit decision making, administration reporting, and research. Here, we share several desiderata pertaining to development and usage of NLP systems, derived from two decades of experience implementing clinical NLP at the Mayo Clinic, to inform the healthcare AI community. Using a framework, we developed as an example implementation, the desiderata emphasize the importance of a user-friendly platform, efficient collection of domain expert inputs, seamless integration with clinical data, and a highly scalable computing infrastructure.