ArticleTranslational vision science & technology2017
Validation of the Total Visual Acuity Extraction Algorithm (TOVA) for Automated Extraction of Visual Acuity Data From Free Text, Unstructured Clinical Records.
Article in Translational vision science & technology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- A four-year retrospective surgical case series examining postoperative complications following Removal of Silicone Oil (ROSO) scored using the Complications of Retinal Detachment Surgery (CORDS) severity classification tool.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Article
- Endoscope-assisted vitrectomy using a 25-gauge system for endophthalmitis: a case series.BMC ophthalmology · 2026Article
- Zero-shot LLM-based visual acuity extraction: a pilot study.BMC ophthalmology · 2025Article
- Visual Acuity: Assessment of Data Quality and Usability in an Electronic Health Record System.Ophthalmology science · 2023Article
- Leveraging weak supervision to perform named entity recognition in electronic health records progress notes to identify the ophthalmology exam.International journal of medical informatics · 2022Article
- Therapeutic and tectonic keratoplasty with simple cryopreserved remnants of donor corneas: an 11 year retrospective case series.Scientific reports · 2022Article
- Applications of natural language processing in ophthalmology: present and future.Frontiers in medicine · 2022Review
- Retinal Detachment After Endophthalmitis: Risk Factors and Outcomes.Clinical ophthalmology (Auckland, N.Z.) · 2021Article
- Text Processing for Detection of Fungal Ocular Involvement in Critical Care Patients: Cross-Sectional Study.Journal of medical Internet research · 2020Article
- Natural Language Processing to Quantify Microbial Keratitis Measurements.Ophthalmology · 2019Article
- Automated Recognition of Visual Acuity Measurements in Ophthalmology Clinical Notes Using Deep Learning.Ophthalmology scienceArticle
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5 authors.
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Abstract
purposeWith increasing volumes of electronic health record data, algorithm-driven extraction may aid manual extraction. Visual acuity often is extracted manually in vision research. The total visual acuity extraction algorithm (TOVA) is presented and validated for automated extraction of visual acuity from free text, unstructured clinical notes.
methodsConsecutive inpatient ophthalmology notes over an 8-year period from the University of Washington healthcare system in Seattle, WA were used for validation of TOVA. The total visual acuity extraction algorithm applied natural language processing to recognize Snellen visual acuity in free text notes and assign laterality. The best corrected measurement was determined for each eye and converted to logMAR. The algorithm was validated against manual extraction of a subset of notes.
resultsA total of 6266 clinical records were obtained giving 12,452 data points. In a subset of 644 validated notes, comparison of manually extracted data versus TOVA output showed 95% concordance. Interrater reliability testing gave κ statistics of 0.94 (95% confidence interval [CI], 0.89-0.99), 0.96 (95% CI, 0.94-0.98), 0.95 (95% CI, 0.92-0.98), and 0.94 (95% CI, 0.90-0.98) for acuity numerators, denominators, adjustments, and signs, respectively. Pearson correlation coefficient was 0.983. Linear regression showed an
conclusionsThe total visual acuity extraction algorithm is a novel tool for extraction of visual acuity from free text, unstructured clinical notes and provides an open source method of data extraction. TRANSLATIONAL RELEVANCE: Automated visual acuity extraction through natural language processing can be a valuable tool for data extraction from free text ophthalmology notes.
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