Automating Quality Control for Structured Standardized Radiology Reports Using Text Analysis.
| Type of publication: | Inproceedings |
| Citation: | |
| Publication status: | Published |
| Booktitle: | Medical Informatics Europe 2020 |
| Series: | Studies in Health Technology and Informatics |
| Volume: | 270 |
| Year: | 2020 |
| Month: | June |
| Pages: | 58--62 |
| Publisher: | IOS Press |
| Location: | Geneva |
| ISBN: | 978-1-64368-083-5 |
| URL: | https://pubmed.ncbi.nlm.nih.go... |
| DOI: | 10.3233/SHTI200122 |
| Abstract: | Radiology reports describe the findings of a radiologist in an imaging examination, produced for another clinician in order to answer to a clinical indication. Sometimes, the report does not fully answer the question asked, despite guidelines for the radiologist. In this article, a system that controls the quality of reports automatically is described. It notably maps the free text onto MeSH terms and checks if the anatomy and disease terms match in the indication and conclusion of a report. The agreement between manual checks of experienced radiologists and the system is high with automatic checks requiring only a fraction of time. Being able to quality control all reports has the potential to improve report quality and thus limit misunderstandings, loosing time for requesting more information and possibly avoid medical mistakes. |
| Keywords: | Natural Language Processing |
| Authors | |
| Added by: | [] |
| Total mark: | 0 |
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