Open AccessDevelopment and Validation of a Natural Language Processing Tool to Generate the CONSORT Reporting Checklist for Randomized Clinical Trials
Author(s) -
Fan Wang,
Richard L. Schilsky,
David Page,
Robert M. Califf,
Kei Cheung,
Xiaofei Wang,
Herbert Pang
Publication year - 2020
Publication title -
jama network open
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.278
H-Index - 39
ISSN - 2574-3805
DOI - 10.1001/jamanetworkopen.2020.14661
Subject(s) - checklist , consolidated standards of reporting trials , metric (unit) , randomized controlled trial , set (abstract data type) , clinical trial , medicine , computer science , medical physics , natural language processing , artificial intelligence , data mining , psychology , pathology , operations management , programming language , economics , cognitive psychology
Key Points Question Can natural language processing tools generate a Consolidated Standards of Reporting Trials (CONSORT) reporting checklist automatically for manuscripts of randomized clinical trials? Findings An automated reporting checklist generation tool using natural language processing, CONSORT-NLP, was developed using 158 articles reporting randomized clinical trials; CONSORT-NLP performed well in the validation set evaluation of fully implemented reporting items (28 of 30 items [93%] achieved >90% accuracy, and the remaining 2 of 30 [7%] achieved between 80% and 90% accuracy) and requires on average 23 seconds to complete (human: 11.9-57.6 minutes). Meaning Authors who plan to publish a randomized clinical trial with the CONSORT checklist may save substantial time by using CONSORT-NLP because this tool is an aid in completing the CONSORT checklist.
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