• Korean Journal of Radiology
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• v.23 no.3
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• pp.343-354
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• 2022

Objective: To develop and evaluate a deep learning-based artificial intelligence (AI) model for detecting skull fractures on plain radiographs in children. Materials and Methods: This retrospective multi-center study consisted of a development dataset acquired from two hospitals (n = 149 and 264) and an external test set (n = 95) from a third hospital. Datasets included children with head trauma who underwent both skull radiography and cranial computed tomography (CT). The development dataset was split into training, tuning, and internal test sets in a ratio of 7:1:2. The reference standard for skull fracture was cranial CT. Two radiology residents, a pediatric radiologist, and two emergency physicians participated in a two-session observer study on an external test set with and without AI assistance. We obtained the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity along with their 95% confidence intervals (CIs). Results: The AI model showed an AUROC of 0.922 (95% CI, 0.842-0.969) in the internal test set and 0.870 (95% CI, 0.785-0.930) in the external test set. The model had a sensitivity of 81.1% (95% CI, 64.8%-92.0%) and specificity of 91.3% (95% CI, 79.2%-97.6%) for the internal test set and 78.9% (95% CI, 54.4%-93.9%) and 88.2% (95% CI, 78.7%-94.4%), respectively, for the external test set. With the model's assistance, significant AUROC improvement was observed in radiology residents (pooled results) and emergency physicians (pooled results) with the difference from reading without AI assistance of 0.094 (95% CI, 0.020-0.168; p = 0.012) and 0.069 (95% CI, 0.002-0.136; p = 0.043), respectively, but not in the pediatric radiologist with the difference of 0.008 (95% CI, -0.074-0.090; p = 0.850). Conclusion: A deep learning-based AI model improved the performance of inexperienced radiologists and emergency physicians in diagnosing pediatric skull fractures on plain radiographs.

• Tuberculosis and Respiratory Diseases
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• v.42 no.1
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• pp.84-92
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• 1995

Background: Nasal applied continuous positive airway pressure(CPAP) is a highly effective method of treatment for obstructive sleep apnea syndrome. More than a decade of accumulated experience with this treatment modality confirmed that it is unquestionably the medical treatment of choice for patients with obstructive sleep apnea syndrome. However it takes long time to reach optimal CPAP pressure. To save the time to reach optimal pressure, it is necessary to clarify the time to reach optimal pressure for treatment of obstructive sleep apnea syndrome. Method: CPAP pressure is titrated during an overnight study according to a standardized protocol. Just before the presleep bio-calibration procedures, the technician applies the nasal mask and switches on the clinical CPAP unit. Initial positive for pressure is typically 3.0 centimeters of water pressure. After sleep onset, the technician gradually increases the pressure until sleep-disordered breathing events disappear or become minimal. The pressure must maintain maximal airway patency during both NREM and REM sleep to be considered effective. Before recommending a final pressure setting, sleep recording and oximetry data are reviewed by an American Board of Sleep Medicine certified Sleep Specialist and a Registrered Polysomnographic Technologist. Results: We examined the time required to reach optimal pressure during routine CPAP titration in 127 consecutively evaluated individuals diagnosed with sleep-disordered breathing. Results indicate that 33% of patients required more than four hours to attain satisfactory titration. This indicates that a four-hour session is marginally enough time, at best, to determine a proper CPAP pressure setting. Moreover, 60 of 127 patients required further adjustment after optimal pressure was reached. These additional pressure trials were needed to confirm that higher pressures were not superior for eliminating sleep-disordered breathing events. Conclusions: The data presented underscore the logistical difficulty of titrating CPAP during split-night studies without modifying the titration procedure. Futhermore, the time needed to reach optimal pressure makes it improbable that proper CPAP titration can be performed during a 2-3 hour nap study.