Comment on “Computer algorithm can match physicians’ decisions about blood transfusions”

Of the 4946 patients who received intra-operative blood transfusions, 3604 cases were classified as appropriate and 1342 as inappropriate by expert anesthesiologists based on guidelines of the World Health Organization. In this study, no splitting procedure is described in the materials and methods...

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Vydáno v:Journal of translational medicine Ročník 19; číslo 1; s. 175 - 2
Hlavní autor: De Bruyne, Sander
Médium: Journal Article
Jazyk:angličtina
Vydáno: London BioMed Central 28.04.2021
BioMed Central Ltd
Springer Nature B.V
BMC
Témata:
Algorithms
Biomedical and Life Sciences
Biomedicine
Blood Transfusion
Blood transfusions
Computers
Decision Making
Humans
Letter to the Editor
Machine learning
Medical laboratories
Medicine/Public Health
Neural networks
Physicians
ISSN:1479-5876, 1479-5876
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Abstract Of the 4946 patients who received intra-operative blood transfusions, 3604 cases were classified as appropriate and 1342 as inappropriate by expert anesthesiologists based on guidelines of the World Health Organization. In this study, no splitting procedure is described in the materials and methods section and it is stated that all 4946 data entries were inputted to the model. [...]as can be derived from the supplementary python script, it seems that the model was trained, validated and tested on exactly the same data entries. [...]the reported accuracies in this study are likely biased, have to be interpreted as the results of a potentially overfitted model and cannot be perceived as being per definition valid for independent data samples.
AbstractList Of the 4946 patients who received intra-operative blood transfusions, 3604 cases were classified as appropriate and 1342 as inappropriate by expert anesthesiologists based on guidelines of the World Health Organization. In this study, no splitting procedure is described in the materials and methods section and it is stated that all 4946 data entries were inputted to the model. [...]as can be derived from the supplementary python script, it seems that the model was trained, validated and tested on exactly the same data entries. [...]the reported accuracies in this study are likely biased, have to be interpreted as the results of a potentially overfitted model and cannot be perceived as being per definition valid for independent data samples.
ArticleNumber 175
Audience Academic
Author De Bruyne, Sander
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  organization: Department of Diagnostic Sciences, Ghent University
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References Y Yao (2841_CR1) 2019; 17
S De Bruyne (2841_CR2) 2021; 58
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  publication-title: Crit Rev Clin Lab Sci
  doi: 10.1080/10408363.2020.1828811
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StartPage 175
SubjectTerms Algorithms
Biomedical and Life Sciences
Biomedicine
Blood Transfusion
Blood transfusions
Computers
Decision Making
Humans
Letter to the Editor
Machine learning
Medical laboratories
Medicine/Public Health
Neural networks
Physicians
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Title Comment on “Computer algorithm can match physicians’ decisions about blood transfusions”
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