การเรียนรู้ของเครื่องและการประยุกต์ใช้ทางวิทยาเอ็นโดดอนต์
Keywords:
deep learning, endodontics, machine learning, model evaluation, root canal treatmentAbstract
With developments in computer science and data science, the field of artificial intelligence known as machine learning entered the dental field. It has been used in endodontics, for example, to locate periapical lesions in the radiographs, Identification of the root canal morphology, detection of root fracture etc. The majority of studies employ supervised machine learning, wherein humans provide a labeled input data set for the computer to train using statistical equations, producing intricate mathematical models. Once the created model has proven to be sufficiently efficient, it is then put into use, and its performance is reviewed. Convolutional neural network (CNN) learning techniques are utilized to extract crucial data for model creation from imaging and radiography data, which make up most of the data used in endodontic research. Most research has concluded that machine learning is effective. Enhance decision-making speed while increasing operational precision. It might serve as a supplementary mechanism to improve operational efficiency.
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