Superimposition of the cephalometric tracings obtained before and after treatment of case with mandibular third molar extraction. by Lijuan Liu (136685)

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Typical measurement parameters. by Lijuan Liu (136685)

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Cephalometric measurement points. by Lijuan Liu (136685)

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Posttreatment facial, intraoral photographs, and radiographs of the case with premolar tooth extraction. by Lijuan Liu (136685)

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Anonymized raw cephalometric data. by Lijuan Liu (136685)

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Posttreatment facial, intraoral photographs, and radiographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)

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Comparison of pretreatment cephalometric variables between premolar extraction and mandibular third molar extraction groups. by Lijuan Liu (136685)

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Demographic characteristics of study participants. by Lijuan Liu (136685)

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Results of Analysis of Co-variance (ANCOVA) for change in parameter predicted by treatment group with pre-treatment value as a covariate. * p < 0.05; ** p < 0.01. by Lijuan Liu (136685)

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Comparison of treatment effects between premolar extraction and mandibular third molar extraction groups. * p < 0.05; ** p < 0.01. by Lijuan Liu (136685)

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Comparison of upper and lower arch crowding between premolar extraction group and the mandibular third molar extraction groups. by Lijuan Liu (136685)

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Intraoperative facial and intraoral photographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)

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Pretreatment facial, intraoral photographs, and radiographs of the case with premolar tooth extraction. by Lijuan Liu (136685)

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Pretreatment facial, intraoral photographs, and radiographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)

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Test results for P, R, F1, and OA. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Results of the colorimetric MTT test. by Adela Klezlova (22608008)

“…In the study group, the IOP was statistically significantly lower by 29% at the end of the follow-up compared to the preoperative measurements (<i><i>p</i></i> = 0.009). …”

Generalized estimating equation (GEE) model results on the influence of weekly weather conditions and air quality on weekly visitation to federal parks and protected areas (PPA), i... by Kira Minehart (21029571)

Generalized estimating equation (GEE) model results on the influence of weekly weather conditions and air quality on weekly visitation to local parks and protected areas (PPA), inc... by Kira Minehart (21029571)

Generalized estimating equation (GEE) model results on the influence of weekly weather conditions and air quality on weekly visitation to state parks and protected areas (PPA), inc... by Kira Minehart (21029571)

An infographic outlining the data used for each analysis. by Shelby L. Sturrock (10751675)

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