Clinical natural language processing for radiation oncology: a review and practical primer
Published in International Journal of Radiation Oncology* Biology* Physics 110 (3), 641-655, 2021, 2021
Recommended citation: MD Danielle S Bitterman, PhD Timothy A Miller, MD Raymond H Mak, and PhD Guergana K Savova. 2021. Clinical natural language processing for radiation oncology: a review and practical primer. In International Journal of Radiation Oncology* Biology* Physics 110 (3), 641-655, 2021. https://www.redjournal.org/article/S0360-3016(21)00118-8/pdf
Abstract:
Natural language processing (NLP), which aims to convert human language into expressions that can be analyzed by computers, is one of the most rapidly developing and widely used technologies in the field of artificial intelligence. Natural language processing algorithms convert unstructured free text data into structured data that can be extracted and analyzed at scale. In medicine, this unlocking of the rich, expressive data within clinical free text in electronic medical records will help untap the full potential of big data for research and clinical purposes. Recent major NLP algorithmic advances have significantly improved the performance of these algorithms, leading to a surge in academic and industry interest in developing tools to automate information extraction and phenotyping from clinical texts. Thus, these technologies are poised to transform medical research and alter clinical practices in the future. Radiation …