@conference{43,
  keywords = {Metadata, Artificial Intelligence, Radiology, Radiology Reports},
  author = {Zola Mahlaza and Ernest Zulu and Lighton Phiri},
  title = {Radiology report terminology to characterise reports in Southern Africa},
  abstract = {There is a shortage of trained radiologists in Southern African countries such as Zambia. The shortage calls for the use of artificial intelligence to bolster the efforts of the few practising radiologists to improve efficiency. Such AI-guided tools require knowledge on how to author good quality reports. Since there is no normative standard for Zambian reports, metadata is required to annotate existing reports to determine characteristics of good reports. As there are no Zambian guidelines for the information to be included in reports, we analyse papers, international guidelines, published structured reports, and existing structured reporting templates to create contemporary and international radiology report terminology, as a first step towards metadata. We identified 3199 terms from vetted templates published by the Radiological Society of North America's RadReport Template Library. We also augmented them with 323 terms extracted from published papers (71% were manually annotated with SNOMED codes for quality assurance).},
  year = {2023},
  journal = {17th International Conference on Metadata and Semantics Research},
  month = {10/2023},
  publisher = {Springer Nature},
  address = {Milan, Italy},
}