ABSTRACT
BACKGROUND: Artificial Intelligence has created a huge impact in different areas of dentistry. Automated cephalometric analysis is one of the major applications of artificial intelligence in the field of orthodontics. Various automated cephalometric software have been developed which utilizes artificial intelligence and claim to be reliable. The purpose of this study was to compare the linear and angular cephalometric measurements obtained from web-based fully automated Artificial Intelligence (AI) driven platform "WebCeph"™ with that from manual tracing and evaluate the validity and reliability of automated cephalometric measurements obtained from "WebCeph"™. METHODS: Thirty pre-treatment lateral cephalograms of patients were randomly selected. For manual tracing, digital images of same cephalograms were printed using compatible X-ray printer. After calibration, a total of 18 landmarks was plotted and 12 measurements (8 angular and 4 linear) were obtained using standard protocols. The digital images of each cephalogram were uploaded to "WebCeph"™ server. After image calibration, the automated cephalometric measurements obtained through AI digitization were downloaded for each image. Intraclass correlation coefficient (ICC) was used to determine agreement between the measurements obtained from two methods. ICC value < 0.75 was considered as poor to moderate agreement while an ICC value between 0.75 and 0.90 was considered as good agreement. Agreement was rated as excellent when ICC value > 0.90 was obtained. RESULTS: All the measurements had ICC value above 0.75. A higher ICC value > 0.9 was obtained for seven parameters i.e. ANB, FMA, IMPA/L1 to MP (°), LL to E-line, L1 to NB (mm), L1 to NB (°), S-N to Go-Gn whereas five parameters i.e. UL to E-line, U1 to NA (mm), SNA, SNB, U1 to NA (°) showed ICC value between 0.75 and 0.90. CONCLUSION: A good agreement was found between the cephalometric measurements obtained from "WebCeph"™ and manual tracing.
Subject(s)
Artificial Intelligence , Orthodontics , Cephalometry/methods , Humans , Internet , Reproducibility of ResultsABSTRACT
BACKGROUND: The risk of losing traditional knowledge of medicinal plants and their use and conservation is very high. Documenting knowledge on distribution and use of medicinal plants by different ethnic groups and at spatial scale on a single platform is important from a conservation planning and management perspective. The sustainable use, continuous practice, and safeguarding of traditional knowledge are essential. Communication of such knowledge among scientists and policy makers at local and global level is equally important, as the available information at present is limited and scattered in Nepal. METHODS: In this paper, we aimed to address these shortcomings by cataloguing medicinal plants used by indigenous ethnic groups in Nepal through a systematic review of over 275 pertinent publications published between 1975 and July 2021. The review was complemented by field visits made in 21 districts. We determined the ethnomedicinal plants hotspots across the country and depicted them in heatmaps. RESULTS: The heatmaps show spatial hotspots and sites of poor ethnomedicinal plant use documentation, which is useful for evaluating the interaction of geographical and ethnobotanical variables. Mid-hills and mountainous areas of Nepal hold the highest number of medicinal plant species in use, which could be possibly associated with the presence of higher human population and diverse ethnic groups in these areas. CONCLUSION: Given the increasing concern about losing medicinal plants due to changing ecological, social, and climatic conditions, the results of this paper may be important for better understanding of how medicinal plants in use are distributed across the country and often linked to specific ethnic groups.
