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Coronary Artery Disease Reporting and Data System (CAD-RADS) has been proposed to achieve such standardization by implementing a strict template-based report writing and assignment of a score between 0 and 5 indicating the severity of coronary artery lesions. Even after its introduction, free-form unstructured report writing remains popular among radiologists. In this work, we present our attempts at bridging the gap between structured and unstructured reporting by natural language processing. We present machine learning models that while being trained only on structured reports, can predict CAD-RADS scores by analysis of free-text of unstructured radiology reports. The best model achieves 98% accuracy on structured reports and 92% 1-margin accuracy (difference of<jats:inline-formula content-type=\"math\/tex\"><jats:tex-math notation=\"TeX\" version=\"MathJax\">\\le<\/jats:tex-math><\/jats:inline-formula>1 in the predicted and the actual scores) for free-form unstructured reports. Our model also performs well under very difficult circumstances including nuanced and widely varying terminology used for reporting cardiovascular functions and diseases, scarcity of labeled data for training our model, and uneven class label distribution.<\/jats:p>","DOI":"10.1145\/3474831","type":"journal-article","created":{"date-parts":[[2021,10,17]],"date-time":"2021-10-17T01:39:53Z","timestamp":1634434793000},"page":"1-20","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Bridging the Gap between Structured and Free-form Radiology Reporting: A Case-study on Coronary CT Angiography"],"prefix":"10.1145","volume":"3","author":[{"given":"Amara","family":"Tariq","sequence":"first","affiliation":[{"name":"Department of Biomedical Informatics, Emory University, USA"}]},{"given":"Marly","family":"Van Assen","sequence":"additional","affiliation":[{"name":"Department of Radiology, Emory University, USA"}]},{"given":"Carlo N.","family":"De Cecco","sequence":"additional","affiliation":[{"name":"Department of Radiology, Emory University, USA"}]},{"given":"Imon","family":"Banerjee","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Emory University, USA"}]}],"member":"320","published-online":{"date-parts":[[2021,10,15]]},"reference":[{"issue":"117","key":"e_1_3_2_2_2","article-title":"The validity and applicability of CAD-RADS in the management of patients with coronary artery disease","volume":"10","author":"Abd Mohammad","year":"2019","unstructured":"Mohammad Abd, Alkhalik Basha, Sameh Abdelaziz Aly, Ahmad Abdel, Azim Ismail, and Hanan A. 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