Natural Language Processing (NLP) is a prevalent method for supplying data to clinical research and decision-making by extracting information from electronic medical records. While numerous textbooks and tutorials detail specific algorithms and applications for text processing, algorithmic knowledge is only one component of a successful NLP project.
Drawing from available literature, this paper presents a stepwise approach that applies the Systems Development Life Cycle (SDLC) to projects relying on data extraction through language processing. This methodology emphasizes various stages of the project, including requirements analysis, design, development, testing, and maintenance, ensuring the successful implementation and continuous optimization of NLP systems.
Blogger's Review: The systematic methodology presented in this paper provides a clear framework for the successful implementation of NLP projects, highlighting critical factors beyond algorithms, such as requirements analysis and system testing, which are vital for enhancing the efficiency of clinical research.