دورية أكاديمية
Natural language processing in narrative breast radiology reporting in University Malaya Medical Centre.
| العنوان: | Natural language processing in narrative breast radiology reporting in University Malaya Medical Centre. |
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| المؤلفون: | Tan WM; Data Science and Bioinformatics Laboratory, Institute of Biological Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia., Ng WL; Department of Biomedical Imaging, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia., Ganggayah MD; Data Science and Bioinformatics Laboratory, Institute of Biological Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia., Hoe VCW; Department of Social and Preventive Medicine, Universiti Malaya, Kuala Lumpur, Malaysia., Rahmat K; Department of Biomedical Imaging, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia., Zaini HS; Department of Information Technology, University of Malaya Medical Centre, Kuala Lumpur, Malaysia., Mohd Taib NA; Department of Surgery, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia., Dhillon SK; Data Science and Bioinformatics Laboratory, Institute of Biological Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia. |
| المصدر: | Health informatics journal [Health Informatics J] 2023 Jul-Sep; Vol. 29 (3), pp. 14604582231203763. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: SAGE Publications Country of Publication: England NLM ID: 100883604 Publication Model: Print Cited Medium: Internet ISSN: 1741-2811 (Electronic) Linking ISSN: 14604582 NLM ISO Abbreviation: Health Informatics J Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: London : SAGE Publications Original Publication: Sheffield, UK : Sheffield Academic Press, [1997- |
| مواضيع طبية MeSH: | Natural Language Processing* , Radiology*, Humans ; Malaysia ; Universities ; Data Mining |
| مستخلص: | Radiology reporting is narrative, and its content depends on the clinician's ability to interpret the images accurately. A tertiary hospital, such as anonymous institute, focuses on writing reports narratively as part of training for medical personnel. Nevertheless, free-text reports make it inconvenient to extract information for clinical audits and data mining. Therefore, we aim to convert unstructured breast radiology reports into structured formats using natural language processing (NLP) algorithm. This study used 327 de-identified breast radiology reports from the anonymous institute. The radiologist identified the significant data elements to be extracted. Our NLP algorithm achieved 97% and 94.9% accuracy in training and testing data, respectively. Henceforth, the structured information was used to build the predictive model for predicting the value of the BIRADS category. The model based on random forest generated the highest accuracy of 92%. Our study not only fulfilled the demands of clinicians by enhancing communication between medical personnel, but it also demonstrated the usefulness of mineable structured data in yielding significant insights. |
| فهرسة مساهمة: | Keywords: information extraction; natural language processing; radiology reporting; rule-based; text mining |
| تواريخ الأحداث: | Date Created: 20230923 Date Completed: 20231102 Latest Revision: 20231107 |
| رمز التحديث: | 20240628 |
| DOI: | 10.1177/14604582231203763 |
| PMID: | 37740904 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1741-2811 |
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| DOI: | 10.1177/14604582231203763 |