| dc.contributor.author | Pollard, Tom | |
| dc.contributor.author | Sounack, Thomas | |
| dc.contributor.author | Gao, Catherine A | |
| dc.contributor.author | Celi, Leo Anthony | |
| dc.contributor.author | Lindvall, Charlotta | |
| dc.contributor.author | Lee, Hyeonhoon | |
| dc.contributor.author | Lee, Hyung-Chul | |
| dc.contributor.author | Moons, Karel GM | |
| dc.contributor.author | Collins, Gary S | |
| dc.date.accessioned | 2026-04-28T15:42:55Z | |
| dc.date.available | 2026-04-28T15:42:55Z | |
| dc.date.issued | 2026-02-10 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/165713 | |
| dc.description.abstract | The Transparent Reporting of a multivariable prediction model of Individual Prognosis Or Diagnosis (TRIPOD) statement was published to improve the reporting and critical appraisal of prediction model studies for diagnosis and prognosis. This paper describes the processes and methods that will be used to develop an extension to the TRIPOD statement (TRIPOD-Code) for the management of code associated with prediction model studies. TRIPOD-Code focuses specifically on the transparent reporting of analytical code used in prediction model studies, including code for data preprocessing, model development, and model evaluation. | en_US |
| dc.language.iso | en | |
| dc.publisher | Springer Science and Business Media LLC | en_US |
| dc.relation.isversionof | https://doi.org/10.1186/s41512-025-00217-4 | en_US |
| dc.rights | Creative Commons Attribution | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.source | Springer Science and Business Media LLC | en_US |
| dc.title | Protocol for development of a reporting guideline (TRIPOD-Code) for code repositories associated with diagnostic and prognostic prediction model studies | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Pollard, T., Sounack, T., Gao, C.A. et al. Protocol for development of a reporting guideline (TRIPOD-Code) for code repositories associated with diagnostic and prognostic prediction model studies. Diagn Progn Res 10, 4 (2026). | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | en_US |
| dc.relation.journal | Diagnostic and Prognostic Research | en_US |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dc.date.updated | 2026-04-28T15:37:31Z | |
| dspace.orderedauthors | Pollard, T; Sounack, T; Gao, CA; Celi, LA; Lindvall, C; Lee, H; Lee, H-C; Moons, KGM; Collins, GS | en_US |
| dspace.date.submission | 2026-04-28T15:37:33Z | |
| mit.journal.volume | 10 | en_US |
| mit.journal.issue | 4 | en_US |
| mit.license | PUBLISHER_CC | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |