How successful is the CatBoost classifier in diagnosing different dental anomalies in patients via sella turcica and vertebral morphologic alteration?

Background: To investigate how successfully the classification of patients with and without dental anomalies was achieved through four experiments involving different dental anomalies.

Methods: Lateral cephalometric radiographs (LCRs) from 526 individuals aged between 14 and 22 years were included. Four experiments involving different dental anomalies were created.

Determination of growth and developmental stages in hand-wrist radiographs : Can fractal analysis in combination with artificial intelligence be used?

Purpose: The goal of this work was to assess the classification of maturation stage using artificial intelligence (AI) classifiers.

Methods: Hand-wrist radiographs (HWRs) from 1067 individuals aged between 7 and 18 years were included. Fifteen regions of interest were selected for fractal dimension (FD) analysis.