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Prediction of oral food challenge outcomes via ensemble learning

Zhang, Justin, Lee, Deborah, Jungles, Kylie, Shaltis, Diane, Najarian, Kayvan, Ravikumar, Rajan, Sanders, Georgiana, Gryak, Jonathan·2023·Informatics in Medicine Unlocked
DOI 10.1016/j.imu.2022.101142
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Crossref · 10.1016/j.imu.2022.101142

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Image 1
CC-BY-NC-ND · From the PDF
Fig. 1 A schematic diagram of the proposed method.
Fig. 1 A schematic diagram of the proposed method.CC-BY-NC-ND · From the PDF
Fig. 2 (a) The partitioning of the dataset; (b) the construction of the cross-validation and ensemble models.
Fig. 2 (a) The partitioning of the dataset; (b) the construction of the cross-validation and ensemble models.CC-BY-NC-ND · From the PDF
Fig. 3 Mean mRMR feature rankings for peanut OFCs. Lower rankings are better.
Fig. 3 Mean mRMR feature rankings for peanut OFCs. Lower rankings are better.CC-BY-NC-ND · From the PDF
Fig. 4 Mean mRMR feature rankings for egg OFCs. Lower rankings are better.
Fig. 4 Mean mRMR feature rankings for egg OFCs. Lower rankings are better.CC-BY-NC-ND · From the PDF
Fig. 5 Mean mRMR feature rankings for milk OFCs. Lower rankings are better.
Fig. 5 Mean mRMR feature rankings for milk OFCs. Lower rankings are better.CC-BY-NC-ND · From the PDF
Fig. 6 Mean SHAP values for peanut OFCs, coded by class. Larger values correspond to greater predictive contributions. Color codings can be observed in the web version of this article.
Fig. 6 Mean SHAP values for peanut OFCs, coded by class. Larger values correspond to greater predictive contributions. Color codings can be observed in the web version of this article.CC-BY-NC-ND · From the PDF
Fig. 7 Mean SHAP values for egg OFCs, coded by class. Larger values correspond to greater predictive contributions. Color codings can be observed in the web version of this article.
Fig. 7 Mean SHAP values for egg OFCs, coded by class. Larger values correspond to greater predictive contributions. Color codings can be observed in the web version of this article.CC-BY-NC-ND · From the PDF
Fig. 8 Mean SHAP values for milk OFCs, coded by class. Larger values correspond to greater predictive contributions. Color codings can be observed in the web version of this article.
Fig. 8 Mean SHAP values for milk OFCs, coded by class. Larger values correspond to greater predictive contributions. Color codings can be observed in the web version of this article.CC-BY-NC-ND · From the PDF

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Research works printed but not linked: 31

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Metadata

Authors
Zhang, J., Lee, D., Jungles, K., Shaltis, D., Najarian, K., Ravikumar, R., Sanders, G., & Gryak, J.
ORCID
Gryak, Jonathan
Venue
Informatics in Medicine Unlocked
Publisher
Elsevier BV
Published
2023
Volume
36
Pages
101142
ISSN
2352-9148
DOI
10.1016/j.imu.2022.101142
Cited by
11
References
0
Language
en
Licence
Funders
University of Michigan

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CoChat. (2026). Citation check: Prediction of oral food challenge outcomes via ensemble learning. https://app.cochat.ai/papers/10.1016/j.imu.2022.101142
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Zhang, J., Lee, D., Jungles, K., Shaltis, D., Najarian, K., Ravikumar, R., Sanders, G., & Gryak, J. (2023). Prediction of oral food challenge outcomes via ensemble learning. Informatics in Medicine Unlocked. https://doi.org/10.1016/j.imu.2022.101142