Exploiting temporal relationships in the prediction of mortality
- PMID: 33328073
- PMCID: PMC8054437
- DOI: 10.1016/S2589-7500(20)30056-X
Exploiting temporal relationships in the prediction of mortality
Conflict of interest statement
We declare no competing interests.
Comment on
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Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records.Lancet Digit Health. 2020 Apr;2(4):e179-e191. doi: 10.1016/S2589-7500(20)30018-2. Epub 2020 Mar 12. Lancet Digit Health. 2020. PMID: 33328078
References
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- Thorsen-Meyer H-C, Nielsen AB, Nielsen AP, et al. Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records. Lancet Digital Health 2020; published online March 12. 10.1016/S2589-7500(20)30018-2. - DOI - PubMed
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- Collins GS, Reitsma JB, Altman DG, Moons KG. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. Eur Urol 2015; 67: 1142–51. - PubMed
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