Development of a software complex for the diagnosis of dentoalveolar anomalies using neural networks
This addresses the problem of treatment planning for dental anomalies, but appears incremental as it applies existing neural network methods to a specific medical domain without novel breakthroughs.
The researchers tackled the problem of diagnosing dentoalveolar anomalies by developing a software complex that uses convolutional neural networks to decode teleradiographic images, but no concrete results or numbers are provided in the abstract.
This article describes the goals and objectives of developing a software complex for planning the treatment of dentoalveolar anomalies, the architecture of the software complex as interacting components for treatment planning, as well as the principle of using algorithms using convolutional neural networks within the software complex for a component that solves the problem of decoding a teleradiographic image.