{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T02:31:33Z","timestamp":1778812293629,"version":"3.51.4"},"reference-count":23,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2020,6,11]],"date-time":"2020-06-11T00:00:00Z","timestamp":1591833600000},"content-version":"vor","delay-in-days":162,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01LM10817"],"award-info":[{"award-number":["R01LM10817"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Clinical case reports are the \u2018eyewitness reports\u2019 of medicine and provide a valuable, unique, albeit noisy and underutilized type of evidence. Generally, a case report has a single main finding that represents the reason for writing up the report in the first place. However, no one has previously created an automatic way of identifying main finding sentences in case reports. We previously created a manual corpus of main finding sentences extracted from the abstracts and full text of clinical case reports. Here, we have utilized the corpus to create a machine learning-based model that automatically predicts which sentence(s) from abstracts state the main finding. The model has been evaluated on a separate manual corpus of clinical case reports and found to have good performance. This is a step toward setting up a retrieval system in which, given one case report, one can find other case reports that report the same or very similar main findings. The code and necessary files to run the main finding model can be downloaded from https:\/\/github.com\/qi29\/main_ finding_recognition, released under the Apache License, Version 2.0.<\/jats:p>","DOI":"10.1093\/database\/baaa041","type":"journal-article","created":{"date-parts":[[2020,5,8]],"date-time":"2020-05-08T11:09:44Z","timestamp":1588936184000},"source":"Crossref","is-referenced-by-count":11,"title":["Identifying main finding sentences in clinical case reports"],"prefix":"10.1093","volume":"2020","author":[{"given":"Mengqi","family":"Luo","sequence":"first","affiliation":[{"name":"Department of Psychiatry and Psychiatric Institute, University of Illinois College of Medicine, Chicago, IL 60612, USA"},{"name":"School of Information Management, Wuhan University, Wuhan, Hubei 430072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aaron M","family":"Cohen","sequence":"first","affiliation":[{"name":"Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sidharth","family":"Addepalli","sequence":"first","affiliation":[{"name":"Department of Psychiatry and Psychiatric Institute, University of Illinois College of Medicine, Chicago, IL 60612, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neil R","family":"Smalheiser","sequence":"first","affiliation":[{"name":"Department of Psychiatry and Psychiatric Institute, University of Illinois College of Medicine, Chicago, IL 60612, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2020,6,11]]},"reference":[{"key":"2020061104343213900_ref1","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1177\/014107689909200401","article-title":"Case reports in an evidence-based world","volume":"92","author":"Vandenbroucke","year":"1999","journal-title":"J. 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