Do It Right! A Methodology for Successful NLP System Development
For researchers and practitioners developing NLP systems for clinical data extraction, this provides a structured process framework, but it is largely a synthesis of existing literature without empirical validation.
This paper presents a stepwise methodology applying the Systems Development Life Cycle to NLP projects in clinical settings, aiming to improve project success beyond algorithmic knowledge. No concrete results are reported.
Natural language processing (NLP) is a common method for supplying data to clinical research and decision making by extracting information from electronic medical records. Numerous textbooks and tutorials describe specific algorithms and applications for text processing, yet algorithmic knowledge is only one ingredient of a successful NLP project. Drawing on the available literature, this paper presents a stepwise approach that applies the Systems Development Life Cycle (SDLC) to projects that rely on data extraction through language processing.