Predicting the risks of kidney failure and death in adults with moderate to severe chronic kidney disease

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Standard

Predicting the risks of kidney failure and death in adults with moderate to severe chronic kidney disease. / Gerds, Thomas Alexander; Ravani, Pietro.

I: BMJ, Bind 385, q721, 2024.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Gerds, TA & Ravani, P 2024, 'Predicting the risks of kidney failure and death in adults with moderate to severe chronic kidney disease', BMJ, bind 385, q721. https://doi.org/10.1136/bmj.q721

APA

Gerds, T. A., & Ravani, P. (2024). Predicting the risks of kidney failure and death in adults with moderate to severe chronic kidney disease. BMJ, 385, [q721]. https://doi.org/10.1136/bmj.q721

Vancouver

Gerds TA, Ravani P. Predicting the risks of kidney failure and death in adults with moderate to severe chronic kidney disease. BMJ. 2024;385. q721. https://doi.org/10.1136/bmj.q721

Author

Gerds, Thomas Alexander ; Ravani, Pietro. / Predicting the risks of kidney failure and death in adults with moderate to severe chronic kidney disease. I: BMJ. 2024 ; Bind 385.

Bibtex

@article{86d59063ea9141ccaced020627d3ec79,
title = "Predicting the risks of kidney failure and death in adults with moderate to severe chronic kidney disease",
abstract = "The risk prediction model for kidney failure and death in people with chronic kidney disease (CKD) presented in the linked study is a super learner. A super learner is an algorithm that repeatedly splits the data into training and test sets and then chooses the best performing model from a list of candidate prediction models. This article describes why and how the super learner was implemented in the linked study.",
author = "Gerds, {Thomas Alexander} and Pietro Ravani",
year = "2024",
doi = "10.1136/bmj.q721",
language = "English",
volume = "385",
journal = "The BMJ",
issn = "0959-8146",
publisher = "BMJ Publishing Group",

}

RIS

TY - JOUR

T1 - Predicting the risks of kidney failure and death in adults with moderate to severe chronic kidney disease

AU - Gerds, Thomas Alexander

AU - Ravani, Pietro

PY - 2024

Y1 - 2024

N2 - The risk prediction model for kidney failure and death in people with chronic kidney disease (CKD) presented in the linked study is a super learner. A super learner is an algorithm that repeatedly splits the data into training and test sets and then chooses the best performing model from a list of candidate prediction models. This article describes why and how the super learner was implemented in the linked study.

AB - The risk prediction model for kidney failure and death in people with chronic kidney disease (CKD) presented in the linked study is a super learner. A super learner is an algorithm that repeatedly splits the data into training and test sets and then chooses the best performing model from a list of candidate prediction models. This article describes why and how the super learner was implemented in the linked study.

U2 - 10.1136/bmj.q721

DO - 10.1136/bmj.q721

M3 - Journal article

C2 - 38621785

AN - SCOPUS:85190765126

VL - 385

JO - The BMJ

JF - The BMJ

SN - 0959-8146

M1 - q721

ER -

ID: 393793965