Deep learning algorithms for identifying 79 dental implant types

Purpose@#This study aimed to evaluate the accuracy and clinical usability of an identification model using deep learning for 79 dental implant types. @*Materials and Methods@#A total of 45396 implant fixture images were collected through panoramic radiographs of patients who received implant treatment from 2001 to 2020 at 30 dental clinics. The collected implant images were 79 types from 18 manufacturers. EfficientNet and Meta Pseudo Labels algorithms were used. For EfficientNet, EfficientNet-B0 and EfficientNet-B4 were used as submodels. For Meta Pseudo Labels, two models were applied according to the widen factor. Top 1 accuracy was measured for EfficientNet and top 1 and top 5 accuracy for Meta Pseudo Labels were measured. @*Results@#EfficientNet-B0 and EfficientNet-B4 showed top 1 accuracy of 89.4. Meta Pseudo Labels 1 showed top 1 accuracy of 87.96, and Meta pseudo labels 2 with increased widen factor showed 88.35. In Top5 Accuracy, the score of Meta Pseudo Labels 1 was 97.90, which was 0.11% higher than 97.79 of Meta Pseudo Labels 2. @*Conclusion@#All four deep learning algorithms used for implant identification in this study showed close to 90% accuracy. In order to increase the clinical applicability of deep learning for implant identification, it will be necessary to collect a wider amount of data and develop a fine-tuned algorithm for implant identification.

A Case of Chemical Pneumonitis Induced by Teflon Inhalation / 대한내과학회지

Chemical pneumonitis is defined as lung irritation caused by inhalation of substances toxic to the lungs. Acute chemical pneumonitis causes swelling of the lung tissue, movement of fluid into the air spaces in the lung, and a decreased ability to absorb oxygen and eliminate carbon dioxide. Teflon (polytetrafluoroethylene) is a commonly used synthetic fiber or insulator. To our knowledge, chemical pneumonitis and acute respiratory failure induced by Teflon inhalation has not been previously reported in Korea. We experienced a 44-year-old patient who had a cough and dyspnea that were aggravated 10 h after smoking tobacco wet by Teflon for 5 min at his workplace. Upon arrival at the emergency room, his blood pressure was low and his arterial blood gas analysis revealed hypoxemia. A chest radiograph showed diffuse haziness on both mid- to-lower lung fields. Following treatment by conservative therapy, including oxygen supply and steroid use, his condition was relatively good and his chest radiograph normalized.