Journal article
Identifying free-text features to improve automated classification of structured histopathology reports for feline small intestinal disease
Journal of veterinary diagnostic investigation, Vol.30(2), pp.211-217
03/2018
DOI: 10.1177/1040638717744002
PMCID: PMC6505871
PMID: 29188759
Abstract
The histologic evaluation of gastrointestinal (GI) biopsies is the standard for diagnosis of a variety of GI diseases (e.g., inflammatory bowel disease [IBD] and alimentary lymphoma [ALA]). The World Small Animal Veterinary Association (WSAVA) Gastrointestinal International Standardization Group proposed a reporting standard for GI biopsies consisting of a defined set of microscopic features. We compared the machine classification accuracy of free-text microscopic findings with those represented in the WSAVA format with a diagnosis of IBD and ALA. Unstructured free-text duodenal biopsy pathology reports from cats ( n = 60) with a diagnosis of IBD ( n = 20), ALA ( n = 20), or normal ( n = 20) were identified. Biopsy samples from these cases were then scored following the WSAVA guidelines to create a set of structured reports. Three supervised machine-learning algorithms were trained using the structured and then the unstructured reports. Diagnosis classification accuracy for the 3 algorithms was compared using the structured and unstructured reports. Using naive Bayes and neural networks, unstructured information-based models achieved higher diagnostic accuracy (0.90 and 0.88, respectively) compared to the structured information-based models (0.74 and 0.72, respectively). Results suggest that discriminating diagnostic information was lost using current WSAVA microscopic guideline features. Addition of free-text features (number of plasma cells) increased WSAVA auto-classification performance. The methodologies reported in our study represent a way of identifying candidate microscopic features for use in structured histopathology reports.
Details
- Title: Subtitle
- Identifying free-text features to improve automated classification of structured histopathology reports for feline small intestinal disease
- Creators
- Abdullah Awaysheh - Animal Health Diagnostic Center, Cornell University, Ithaca, NY (Elvinger)Jeffrey Wilcke - Animal Health Diagnostic Center, Cornell University, Ithaca, NY (Elvinger)François Elvinger - Animal Health Diagnostic Center, Cornell University, Ithaca, NY (Elvinger)Loren Rees - Animal Health Diagnostic Center, Cornell University, Ithaca, NY (Elvinger)Weiguo Fan - Animal Health Diagnostic Center, Cornell University, Ithaca, NY (Elvinger)Kurt Zimmerman - Animal Health Diagnostic Center, Cornell University, Ithaca, NY (Elvinger)
- Resource Type
- Journal article
- Publication Details
- Journal of veterinary diagnostic investigation, Vol.30(2), pp.211-217
- DOI
- 10.1177/1040638717744002
- PMID
- 29188759
- PMCID
- PMC6505871
- ISSN
- 1040-6387
- eISSN
- 1943-4936
- Language
- English
- Date published
- 03/2018
- Academic Unit
- Business Analytics
- Record Identifier
- 9984083203502771
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