دورية أكاديمية
Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS)
| العنوان: | Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS) |
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| المؤلفون: | Khaled El Emam, Tiffany I Leung, Bradley Malin, William Klement, Gunther Eysenbach |
| المصدر: | Journal of Medical Internet Research, Vol 26, p e52508 (2024) |
| بيانات النشر: | JMIR Publications, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Computer applications to medicine. Medical informatics LCC:Public aspects of medicine |
| مصطلحات موضوعية: | Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270 |
| الوصف: | The number of papers presenting machine learning (ML) models that are being submitted to and published in the Journal of Medical Internet Research and other JMIR Publications journals has steadily increased. Editors and peer reviewers involved in the review process for such manuscripts often go through multiple review cycles to enhance the quality and completeness of reporting. The use of reporting guidelines or checklists can help ensure consistency in the quality of submitted (and published) scientific manuscripts and, for example, avoid instances of missing information. In this Editorial, the editors of JMIR Publications journals discuss the general JMIR Publications policy regarding authors’ application of reporting guidelines and specifically focus on the reporting of ML studies in JMIR Publications journals, using the Consolidated Reporting of Machine Learning Studies (CREMLS) guidelines, with an example of how authors and other journals could use the CREMLS checklist to ensure transparency and rigor in reporting. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1438-8871 |
| Relation: | https://www.jmir.org/2024/1/e52508; https://doaj.org/toc/1438-8871 |
| DOI: | 10.2196/52508 |
| URL الوصول: | https://doaj.org/article/da3ff998251a4ea4ade3f50ed247c71e |
| رقم الأكسشن: | edsdoj.3ff998251a4ea4ade3f50ed247c71e |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 14388871 |
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| DOI: | 10.2196/52508 |