Performance metrics of the machine learning models on the test dataset.

<p>Performance metrics of the machine learning models on the test dataset.</p>

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Bibliographic Details
Main Author:	Kengo Oka (1420585) (author)
Other Authors:	Saki Uemura (22813426) (author), Satoru Morishita (818840) (author), Yukio Yamamoto (365626) (author), Kei Kurita (6158435) (author)
Published:	2025
Subjects:	Cell Biology Biotechnology Developmental Biology tooth alignment images receiver operating characteristic prefer soft foods permutation importance showed construct three algorithms based binary classification highest contributing factor 3 million registered model &# 8217 oral habits revealed determining maxillary protrusion determining deep bite crowding classification model xlink "> malocclusion questionnaire data used xlink "> oral habits maxillary protrusion deep bite questionnaire data determining malocclusion panelists registered important factor sectional data statistical analysis promising approach mouth open motivate patients mixed dentition minimize complications frequently observed four questions f1 score early stage detecting malocclusion detect malocclusion dental image crowding ). common anomaly check dentition approximately 1 90 ). 70 ), 275 boys 244 girls 2021 ).
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