Data Sheet 1_Accurate informatic modeling of tooth enamel pellicle interactions by training substitution matrices with Mat4Pep.doc by Jeremy Horst Keeper (20458274)

Table 1_Development of a prognostic prediction model and visualization system for autologous costal cartilage rhinoplasty: an automated machine learning approach.docx by Aihemaitijiang Niyazi (22355542)

“…We proposed an improved metaheuristic algorithm (INPDOA) for AutoML optimization, validated against 12 CEC2022 benchmark functions. …”

Image 2_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.jpeg by Seungmi Kim (11071440)

Image 1_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.jpeg by Seungmi Kim (11071440)

Data Sheet 2_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.pdf by Seungmi Kim (11071440)

Image 3_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.jpeg by Seungmi Kim (11071440)

Table 1_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.xlsx by Seungmi Kim (11071440)

Data Sheet 1_Development of machine learning models with explainable AI for frailty risk prediction and their web-based application in community public health.pdf by Seungmi Kim (11071440)

The box plot depicting the differential expression validation of the hub genes in the external dataset GSE90081. by Devi Soorya Narayana Sasikumar (22331743)

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The Venn diagram showing the intersection of common genes between WGCNA and DEFeGs. by Devi Soorya Narayana Sasikumar (22331743)

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The classification report of the generated LASSO, RF, and SVM models. by Devi Soorya Narayana Sasikumar (22331743)

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a-c: (a) The nomogram model developed for the prognostic prediction of hub genes from the study. by Devi Soorya Narayana Sasikumar (22331743)

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a-h: The expression differences of the 8 hub genes in 18 immune infiltrating cells. by Devi Soorya Narayana Sasikumar (22331743)

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Illustrative insight into the role of NAMPT and SAT1 in ferroptosis and RA pathogenesis. by Devi Soorya Narayana Sasikumar (22331743)

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(a) The network topology analysis to identify the optimum soft threshold power. by Devi Soorya Narayana Sasikumar (22331743)

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The coregulatory network analysis of the hub genes from the study. by Devi Soorya Narayana Sasikumar (22331743)

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(a) The plot is visualized to understand the association between the number of trees in our RF model and its error rate. by Devi Soorya Narayana Sasikumar (22331743)

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Research process of our study. by Devi Soorya Narayana Sasikumar (22331743)

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Additional files. by Devi Soorya Narayana Sasikumar (22331743)

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(a) The volcano plot of GSE89408, where the red scatter represents the upregulated genes and the blue scatter represents the downregulated genes. (b) The heatmap of GSE89408. by Devi Soorya Narayana Sasikumar (22331743)

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