File:Classification model shows good performance of diagnosing ME-CFS.jpg
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From the study "Developing a Blood Cell-Based Diagnostic Test for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Peripheral Blood Mononuclear Cells"
Summary[edit]
| Description |
English: "Ensemble learner performance on an independent test set breakdown by A) five classes with 84% overall accuracy and B) three classes with overall 91% accuracy. Matrix entries are shown as percentage values. The three-class classification model shows a performance of diagnosing ME/CFS with 91% sensitivity and 93% specificity, MS with 90% sensitivity and 92% specificity, and an overall accuracy at 91% with 87–93% at 95% confidence interval." |
| Date | |
| Source | https://onlinelibrary.wiley.com/doi/10.1002/advs.202302146 |
| Author | Authors of the study: Jiabao Xu, Tiffany Lodge, Caroline Kingdon, James W. L. Strong, John Maclennan, Eliana Lacerda, Slawomir Kujawski, Pawel Zalewski, Wei E. Huang, Karl J. Morten |
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| Date/Time | Thumbnail | Dimensions | User | Comment | |
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| current | 11:12, 15 October 2023 | | 1,000 × 766 (104 KB) | Prototyperspective (talk | contribs) | Uploaded a work by Authors of the study: Jiabao Xu, Tiffany Lodge, Caroline Kingdon, James W. L. Strong, John Maclennan, Eliana Lacerda, Slawomir Kujawski, Pawel Zalewski, Wei E. Huang, Karl J. Morten from https://onlinelibrary.wiley.com/doi/10.1002/advs.202302146 with UploadWizard |
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