ABSTRACT
In this study, a home dental care system consisting of an oral image acquisition device and deep learning models for maxillary and mandibular teeth images is proposed. The presented method not only classifies tooth diseases, but also determines whether a professional dental treatment (NPDT) is required. Additionally, a specially designed oral image acquisition device was developed to perform image acquisition of maxillary and mandibular teeth. Two evaluation metrics, namely, tooth disease and NPDT classifications, were examined using 610 compounded and 5251 tooth images annotated by an experienced dentist with a Doctor of Dental Surgery and another dentist with a Doctor of Dental Medicine. In the tooth disease and NPDT classifications, the proposed system showed accuracies greater than 96% and 89%, respectively. Based on these results, we believe that the proposed system will allow users to effectively manage their dental health by detecting tooth diseases by providing information on the need for dental treatment. Supplementary Information: The online version contains supplementary material available at 10.1007/s12652-021-03366-8.
ABSTRACT
In order to analyze tasks of the death education curriculum for the public, DACUM method was used. A committee for DACUM was gathered and a survey was conducted on professors of health care, humanities and social sciences for an interdisciplinary study. In the survey used to verify the model for death education for the public, a compilation based on difficulty and importance factor shows that the 27 tasks including the psychological changes in terminally ill or suicidal patients, healing of stress, acceptance and understanding of death and suicide prevention were identified as needing to be included in the curriculum. The data thus concluded will have to be reviewed when they are applied to actual education to revise the education program to make it more appropriate.
