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Data for: A systematic review showed no performance benefit of machine learning over logistic regression for clinical prediction models

Main Author: Van Calster, Ben
Other Authors: Ma, Jie, Christodoulou, Evangelia, Steyerberg, Ewout, Verbakel, Jan, Collins, Gary
Format: Dataset
Terbitan: Mendeley , 2019
Subjects:
Machine Learning Algorithm
Data Analysis
Systematic Review
Multivariate Logistical Regression
Clinical Prediction Model
Online Access: https:/data.mendeley.com/datasets/sypyt6c2mc
ctrlnum 0.17632-sypyt6c2mc.1
fullrecord <?xml version="1.0"?> <dc><creator>Van Calster, Ben</creator><title>Data for: A systematic review showed no performance benefit of machine learning over logistic regression for clinical prediction models</title><publisher>Mendeley</publisher><description>The uploaded files are: 1) Excel file containing 6 sheets in respective Order: "Data Extraction" (summarized final data extractions from the three reviewers involved), "Comparison Data" (data related to the comparisons investigated), "Paper level data" (summaries at paper level), "Outcome Event Data" (information with respect to number of events for every outcome investigated within a paper), "Tuning Classification" (data related to the manner of hyperparameter tuning of Machine Learning Algorithms). 2) R script used for the Analysis (In order to read the data, please: Save "Comparison Data", "Paper level data", "Outcome Event Data" Excel sheets as txt files. In the R script srpap: Refers to the "Paper level data" sheet, srevents: Refers to the "Outcome Event Data" sheet and srcompx: Refers to " Comparison data Sheet". 3) Supplementary Material: Including Search String, Tables of data, Figures 4) PRISMA checklist items</description><subject>Machine Learning Algorithm</subject><subject>Data Analysis</subject><subject>Systematic Review</subject><subject>Multivariate Logistical Regression</subject><subject>Clinical Prediction Model</subject><contributor>Ma, Jie</contributor><contributor>Christodoulou, Evangelia</contributor><contributor>Steyerberg, Ewout</contributor><contributor>Verbakel, Jan</contributor><contributor>Collins, Gary</contributor><type>Other:Dataset</type><identifier>10.17632/sypyt6c2mc.1</identifier><rights>Creative Commons Attribution 4.0 International</rights><rights>http://creativecommons.org/licenses/by/4.0</rights><relation>https:/data.mendeley.com/datasets/sypyt6c2mc</relation><date>2019-03-14T05:10:06Z</date><recordID>0.17632-sypyt6c2mc.1</recordID></dc>
format Other:Dataset
Other
author Van Calster, Ben
author2 Ma, Jie
Christodoulou, Evangelia
Steyerberg, Ewout
Verbakel, Jan
Collins, Gary
title Data for: A systematic review showed no performance benefit of machine learning over logistic regression for clinical prediction models
publisher Mendeley
publishDate 2019
topic Machine Learning Algorithm
Data Analysis
Systematic Review
Multivariate Logistical Regression
Clinical Prediction Model
url https:/data.mendeley.com/datasets/sypyt6c2mc
contents The uploaded files are: 1) Excel file containing 6 sheets in respective Order: "Data Extraction" (summarized final data extractions from the three reviewers involved), "Comparison Data" (data related to the comparisons investigated), "Paper level data" (summaries at paper level), "Outcome Event Data" (information with respect to number of events for every outcome investigated within a paper), "Tuning Classification" (data related to the manner of hyperparameter tuning of Machine Learning Algorithms). 2) R script used for the Analysis (In order to read the data, please: Save "Comparison Data", "Paper level data", "Outcome Event Data" Excel sheets as txt files. In the R script srpap: Refers to the "Paper level data" sheet, srevents: Refers to the "Outcome Event Data" sheet and srcompx: Refers to " Comparison data Sheet". 3) Supplementary Material: Including Search String, Tables of data, Figures 4) PRISMA checklist items
id IOS7969.0.17632-sypyt6c2mc.1
institution Universitas Islam Indragiri
affiliation onesearch.perpusnas.go.id
institution_id 804
institution_type library:university
library
library Teknologi Pangan UNISI
library_id 2816
collection Artikel mulono
repository_id 7969
city INDRAGIRI HILIR
province RIAU
shared_to_ipusnas_str 1
repoId IOS7969
first_indexed 2020-04-08T08:33:29Z
last_indexed 2020-04-08T08:33:29Z
recordtype dc
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score 17.538404

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