Leveraging Artificial Intelligence, Natural Language Processing, and Natural Language Generation in Medical Writing

Abstract

Medical writing is a process that generates a variety of documents in the biomedical domain, including but not limited to clinical reports, regulatory reports, protocol documents, patient narratives, plain language summaries, and so on. Medical writing is complex and time-consuming because a writer must refer to multiple sources, sift through a large volume of documents, maintain data integrity, perform review of literature, do interpretation of results, summarize, and so on. These challenges can be addressed and minimized substantially by adopting artificial intelligence, specifically cognitive search, natural language processing (NLP), and natural language generation (NLG) models and other techniques. Given the recent advances in language models for NLG, the time is ripe for a product in the medical writing domain that integrates and automates search capabilities, provides cognitive processing, and generates content using NLG. This white paper takes scientific manuscript writing as an example to provide insights into the way NLP and NLG can augment, automate, and expedite the process of writing a wide variety of biomedical documents. It looks at the current limitations of technology and ways to address those. Finally, it provides recommendations on how these technologies can be used to create a single system or product. Such an approach has the potential to expand into multiple areas in the biomedical domain, with medical writing as the first challenge.