ArticleBioMed research international2022
Rule-Based Information Extraction from Free-Text Pathology Reports Reveals Trends in South African Female Breast Cancer Molecular Subtypes and Ki67 Expression.
Article in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Harnessing data science to control non-communicable diseases in Africa: a systematic review and gap analysis.Communications medicine · 2026Article
- Large language model-based approach for low-cost, rapid and accurate automated extraction of predictive biomarker testing results from Dutch pathology reports.Virchows Archiv : an international journal of pathology · 2026Article
- Application of a Natural Language Processing Framework for Data Extraction From Pathology Reports Across Multiple Cancer Types.Journal of Korean medical science · 2026Article
- Prediction of pathological complete response after neoadjuvant therapy in breast cancer using pretreatment core biopsy pathology reports: a pathology-report-driven model with exploratory clinical-laboratory fusion.Frontiers in oncology · 2026Article
- Article
- Open-Source Hybrid Large Language Model Integrated System for Extraction of Breast Cancer Treatment Pathway From Free-Text Clinical Notes.JCO clinical cancer informatics · 2025Article
- Natural Language Processing Technologies for Public Health in Africa: Scoping Review.Journal of medical Internet research · 2025Article
- Article
- Use of artificial intelligence in healthcare in South Africa: A scoping review.Health SA = SA Gesondheid · 2025Review
- LowerBiology · 2024Article
- FGFR2 genetic variants in women with breast cancer.Molecular medicine reports · 2023Article
- Discordance between PAM50 intrinsic subtyping and immunohistochemistry in South African women with breast cancer.Breast cancer research and treatment · 2023Article
- Artificial intelligence-based prediction for cancer-related outcomes in Africa: Status and potential refinements.Journal of global health · 2022Article
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Authors and funding
5 authors.
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Abstract
Clinical information on molecular subtypes and the Ki67 index is critical for breast cancer (BC) prognosis and personalised treatment plan. Extracting such information into structured data is essential for research, auditing, and cancer incidence reporting and underpins the potential for automated decision support. Herewith, we developed a rule-based natural language processing algorithm that retrieved and extracted important BC parameters from free-text pathology reports towards exploring molecular subtypes and Ki67-proliferation trends. We considered malignant BC pathology reports with different free-text narrative attributes from the South African National Health Laboratory Service. The reports were preprocessed and parsed through the algorithm. Parameters extracted by the algorithm were validated against manually extracted parameters. For all parameters extracted, we obtained accurate annotations of 83-100%, 93-100%, 91-100%, and 92-100% precision, recall,
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