The impact of imputation quality on machine learning classifiers for datasets with missing values

AIX-COVNET Collaboration; Tolou Shadbahr; Michael Roberts; Jan Stanczuk; Julian Gilbey; Philip Teare; Sören Dittmer; Matthew Thorpe; Ramon Viñas Torné; Evis Sala; Pietro Lió; Mishal Patel; Jacobus Preller; Ian Selby; Anna Breger; Jonathan R. Weir-McCall; Effrossyni Gkrania-Klotsas; Anna Korhonen; Emily Jefferson; Georg Langs; Guang Yang; Helmut Prosch; Judith Babar; Lorena Escudero Sánchez; Marcel Wassin; Markus Holzer; Nicholas Walton; James H. F. Rudd; Tuomas Mirtti; Antti Sakari Rannikko; John A. D. Aston; Jing Tang; Carola-Bibiane Schönlieb

doi:10.1038/s43856-023-00356-z

The impact of imputation quality on machine learning classifiers for datasets with missing values

AIX-COVNET Collaboration, Tolou Shadbahr, Michael Roberts, Jan Stanczuk, Julian Gilbey, Philip Teare, Sören Dittmer, Matthew Thorpe, Ramon Viñas Torné, Evis Sala, Pietro Lió, Mishal Patel, Jacobus Preller, Ian Selby, Anna Breger, Jonathan R. Weir-McCall, Effrossyni Gkrania-Klotsas, Anna Korhonen, Emily Jefferson, Georg LangsGuang Yang, Helmut Prosch, Judith Babar, Lorena Escudero Sánchez, Marcel Wassin, Markus Holzer, Nicholas Walton, James H. F. Rudd, Tuomas Mirtti, Antti Sakari Rannikko, John A. D. Aston, Jing Tang, Carola-Bibiane Schönlieb

Research output: Contribution to journal › Article › Scientific › peer-review

Original language	English
Article number	139
Journal	Communications Medicine
Volume	3
Issue number	1
Number of pages	15
ISSN	2730-664X
DOIs	https://doi.org/10.1038/s43856-023-00356-z
Publication status	Published - Oct 2023
MoE publication type	A1 Journal article-refereed

Fields of Science

3121 General medicine, internal medicine and other clinical medicine
3122 Cancers

Access to Document

10.1038/s43856-023-00356-zLicence: CC BY

s43856-023-00356-z (1)Final published version, 2.25 MBLicence: CC BY

Cite this

AIX-COVNET Collaboration, Shadbahr, T., Roberts, M., Stanczuk, J., Gilbey, J., Teare, P., Dittmer, S., Thorpe, M., Torné, R. V., Sala, E., Lió, P., Patel, M., Preller, J., Selby, I., Breger, A., Weir-McCall, J. R., Gkrania-Klotsas, E., Korhonen, A., Jefferson, E., ... Schönlieb, C.-B. (2023). The impact of imputation quality on machine learning classifiers for datasets with missing values. Communications Medicine, 3(1), Article 139. https://doi.org/10.1038/s43856-023-00356-z

@article{cb1455e213f1424e92683184d02c6886,

title = "The impact of imputation quality on machine learning classifiers for datasets with missing values",

keywords = "3121 General medicine, internal medicine and other clinical medicine, 3122 Cancers",

author = "{AIX-COVNET Collaboration} and Tolou Shadbahr and Michael Roberts and Jan Stanczuk and Julian Gilbey and Philip Teare and S{\"o}ren Dittmer and Matthew Thorpe and Torn{\'e}, {Ramon Vi{\~n}as} and Evis Sala and Pietro Li{\'o} and Mishal Patel and Jacobus Preller and Ian Selby and Anna Breger and Weir-McCall, {Jonathan R.} and Effrossyni Gkrania-Klotsas and Anna Korhonen and Emily Jefferson and Georg Langs and Guang Yang and Helmut Prosch and Judith Babar and {Escudero S{\'a}nchez}, Lorena and Marcel Wassin and Markus Holzer and Nicholas Walton and Rudd, {James H. F.} and Tuomas Mirtti and Rannikko, {Antti Sakari} and Aston, {John A. D.} and Jing Tang and Carola-Bibiane Sch{\"o}nlieb",

year = "2023",

month = oct,

doi = "10.1038/s43856-023-00356-z",

language = "English",

volume = "3",

journal = "Communications Medicine",

issn = "2730-664X",

publisher = "Nature Portfolio ",

number = "1",

}

AIX-COVNET Collaboration, Shadbahr, T, Roberts, M, Stanczuk, J, Gilbey, J, Teare, P, Dittmer, S, Thorpe, M, Torné, RV, Sala, E, Lió, P, Patel, M, Preller, J, Selby, I, Breger, A, Weir-McCall, JR, Gkrania-Klotsas, E, Korhonen, A, Jefferson, E, Langs, G, Yang, G, Prosch, H, Babar, J, Escudero Sánchez, L, Wassin, M, Holzer, M, Walton, N, Rudd, JHF, Mirtti, T , Rannikko, AS, Aston, JAD, Tang, J & Schönlieb, C-B 2023, 'The impact of imputation quality on machine learning classifiers for datasets with missing values', Communications Medicine, vol. 3, no. 1, 139. https://doi.org/10.1038/s43856-023-00356-z

TY - JOUR

T1 - The impact of imputation quality on machine learning classifiers for datasets with missing values

AU - AIX-COVNET Collaboration

AU - Shadbahr, Tolou

AU - Roberts, Michael

AU - Stanczuk, Jan

AU - Gilbey, Julian

AU - Teare, Philip

AU - Dittmer, Sören

AU - Thorpe, Matthew

AU - Torné, Ramon Viñas

AU - Sala, Evis

AU - Lió, Pietro

AU - Patel, Mishal

AU - Preller, Jacobus

AU - Selby, Ian

AU - Breger, Anna

AU - Weir-McCall, Jonathan R.

AU - Gkrania-Klotsas, Effrossyni

AU - Korhonen, Anna

AU - Jefferson, Emily

AU - Langs, Georg

AU - Yang, Guang

AU - Prosch, Helmut

AU - Babar, Judith

AU - Escudero Sánchez, Lorena

AU - Wassin, Marcel

AU - Holzer, Markus

AU - Walton, Nicholas

AU - Rudd, James H. F.

AU - Mirtti, Tuomas

AU - Rannikko, Antti Sakari

AU - Aston, John A. D.

AU - Tang, Jing

AU - Schönlieb, Carola-Bibiane

PY - 2023/10

Y1 - 2023/10

KW - 3121 General medicine, internal medicine and other clinical medicine

KW - 3122 Cancers

U2 - 10.1038/s43856-023-00356-z

DO - 10.1038/s43856-023-00356-z

M3 - Article

SN - 2730-664X

VL - 3

JO - Communications Medicine

JF - Communications Medicine

IS - 1

M1 - 139

ER -