Detecting evidence of invasive fungal infections in cytology and histopathology reports enriched with concept-level annotations
- Author(s)
- Rozova, V; Khanina, A; Teng, JC; Teh, JSK; Worth, LJ; Slavin, MA; Thursky, KA; Verspoor, K;
- Journal Title
- Journal of Biomedical Informatics
- Publication Type
- Research article
- Abstract
- Invasive fungal infections (IFIs) are particularly dangerous to high-risk patients with haematological malignancies and are responsible for excessive mortality and delays in cancer therapy. Surveillance of IFI in clinical settings offers an opportunity to identify potential risk factors and evaluate new therapeutic strategies. However, manual surveillance is both time- and resource-intensive. As part of a broader project aimed to develop a system for automated IFI surveillance by leveraging electronic medical records, we present our approach to detecting evidence of IFI in the key diagnostic domain of histopathology. Using natural language processing (NLP), we analysed cytology and histopathology reports to identify IFI-positive reports. We compared a conventional bag-of-words classification model to a method that relies on concept-level annotations. Although the investment to prepare data supporting concept annotations is substantial, extracting targeted information specific to IFI as a pre-processing step increased the performance of the classifier from the PR AUC of 0.84 to 0.92 and enabled model interpretability. We have made publicly available the annotated dataset of 283 reports, the Cytology and Histopathology IFI Reports corpus (CHIFIR), to allow the clinical NLP research community to further build on our results.
- Publisher
- Elsevier
- Keywords
- Humans; *Invasive Fungal Infections/epidemiology; Electronic Health Records; Natural Language Processing; Risk Factors; Concept recognition; Fungal infections; Histopathology reports; Machine learning
- Department(s)
- Infectious Diseases
- PubMed ID
- 36682389
- Publisher's Version
- https://doi.org/10.1016/j.jbi.2023.104293
- Open Access at Publisher's Site
https://doi.org/10.1016/j.jbi.2023.104293- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2023-06-13 07:55:22
Last Modified: 2023-06-13 07:56:08