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( Youjin Chang ),( Ho Cheol Kim ),( Kyung-wook Jo ),( Jae Seung Lee ),( Yeon-mok Oh ),( Sang Do Lee ),( Sei Won Lee ) 대한내과학회 2020 The Korean Journal of Internal Medicine Vol.35 No.1
Background/Aims: Few studies have attempted to interpret unusually high predicted pulmonary function test results. This study aimed to investigate the demographic features of patients with an unusually high predicted pulmonary function. Methods: The demographic data of subjects who underwent pulmonary function testing at a tertiary referral hospital during between January 2011 and December 2011 were retrospectively reviewed. Results: Of the 68,693 included patients, 55 (0.08%) had a percent predicted forced expiratory volume in 1 second or forced vital capacity ≥ 140%. These patients had a relatively older median age (72 years vs. 54 years, p < 0.001), female predominance (65.5% vs. 42.5%, p = 0.001), lower body weight (52.5 kg vs. 64.5 kg, p < 0.001) and shorter height (148.4 cm vs. 164.2 cm, p < 0.001). Furthermore, 6.1% of women older than 80 years with weight < 50 kg and height < 150 cm had a high predicted pulmonary function. Conclusions: A high predicted pulmonary function is not rare among elderly subjects with a small body size. Physicians should consider the demographics of the examinees, especially those of minority populations, particularly as the test results might be determined using an incorrect reference equation.
Validation of the Korean version of the thyroid cancerspecific quality of life questionnaire
Youjin Jeong,Jaekyung Choi,Ah-Leum Ahn,Eun-Jung Oh,Hee-Kyung Oh,Dong-Yung Cho,Hyuk-Jung Kweon,Kyoung Sik Park 대한외과학회 2015 Annals of Surgical Treatment and Research(ASRT) Vol.89 No.6
Purpose: The increasing incidence of thyroid cancer worldwide has drawn attention to the needs for assessing and managing health-related quality of life (HRQoL) of thyroid cancer survivors. We conducted this study to validate the Korean version of the thyroid cancer-specific quality of life (THYCA-QoL) questionnaire. Methods: Data obtained from 227 thyroid cancer survivors were analyzed using standard validity and reliability analysis techniques. Reliability was assessed by measuring internal consistency via Cronbach α coefficient, and validity was assessed by determining the Pearson correlation coefficient between the THYCA-QoL questionnaire and the following relevant assessment tools: the European Organization for Research and Treatment of Cancer QLQ-C30 (EORTC QLQ-C30), the Korean version of Brief Fatigue Inventory (BFI-K), the Korean version of Brief Encounter Psychosocial Instrument (BEPSI-K), Goldberg Short Screening Scale for Anxiety and Depression, and a nine-item Patient Health Questionnaire (PHQ-9). A multitrait scaling analysis was performed to assess each item’s convergent and discriminant validity. Results: The reliability of the THYCA-QoL questionnaire was confirmed by Cronbach α coefficients for multiple-item scales which ranged from 0.54 (sensory) to 0.82 (psychological). Except for a single item (sexual interest), the questionnaire’s validity was established by significant correlation observed between scales in the THYCA-QoL questionnaire and scales used in other assessment tools. A multitrait scaling analysis confirmed that all scales met the recommended psychometric standards. Conclusion: The Korean version of the THYCA-QoL questionnaire is a reliable and valid assessment tool that can be used in combination with the EORTC QLQ-C30 to assess the HRQoL of thyroid cancer survivors in Korea.
Lung Transplantation in Acute Respiratory Distress Syndrome Caused by Influenza Pneumonia
Youjin Chang,Sang Oh Lee,Tae Sun Shim,Sae Hoon Choi,,Hyung Ryul Kim,Yong-Hee Kim,Dong Kwan Kim,Seung-Il Park,Sang-Bum Hong 대한중환자의학회 2015 Acute and Critical Care Vol.30 No.3
Severe acute respiratory distress syndrome (ARDS) is a life-threatening disease with a high mortality rate. Although many therapeutic trials have been performed for improving the mortality of severe ARDS, limited strategies have demonstrated better outcomes. Recently, advanced rescue therapies such as extracorporeal membrane oxygenation (ECMO) made it possible to consider lung transplantation (LTPL) in patients with ARDS, but data is insufficient. We report a 62-year-old man who underwent LTPL due to ARDS with no underlying lung disease. He was admitted to the hospital due to influenza A pneumonia-induced ARDS. Although he was supported by ECMO, he progressively deteriorated. We judged that his lungs were irreversibly damaged and decided he needed to undergo LTPL. Finally, bilateral sequential double-lung transplantation was successfully performed. He has since been alive for three years. Conclusively, we demonstrate that LTPL can be a therapeutic option in patients with severe ARDS refractory to conventional therapies.
CNN-based Gesture Recognition using Motion History Image
( Youjin Koh ),( Taewon Kim ),( Min Hong ),( Yoo-joo Choi ) 한국인터넷정보학회 2020 인터넷정보학회논문지 Vol.21 No.5
In this paper, we present a CNN-based gesture recognition approach which reduces the memory burden of input data. Most of the neural network-based gesture recognition methods have used a sequence of frame images as input data, which cause a memory burden problem. We use a motion history image in order to define a meaningful gesture. The motion history image is a grayscale image into which the temporal motion information is collapsed by synthesizing silhouette images of a user during the period of one meaningful gesture. In this paper, we first summarize the previous traditional approaches and neural network-based approaches for gesture recognition. Then we explain the data preprocessing procedure for making the motion history image and the neural network architecture with three convolution layers for recognizing the meaningful gestures. In the experiments, we trained five types of gestures, namely those for charging power, shooting left,shooting right, kicking left, and kicking right. The accuracy of gesture recognition was measured by adjusting the number of filters in each layer in the proposed network. We use a grayscale image with 240 x 320 resolution which defines one meaningful gesture and achieved a gesture recognition accuracy of 98.24%.