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| 1 | Development of a depression in Parkinson's disease prediction model using machine learning显示文摘BACKGROUND It is important to diagnose depression in Parkinson’s disease(DPD)as soon as possible and identify the predictors of depression to improve quality of life in Parkinson’s disease(PD)patients.AIM To develop a model for predicting DPD based on the support vector machine,while considering sociodemographic factors,health habits,Parkinson's symptoms,sleep behavior disorders,and neuropsychiatric indicators as predictors and provide baseline data for identifying DPD.METHODS This study analyzed 223 of 335 patients who were 60 years or older with PD.Depression was measured using the 30 items of the Geriatric Depression Scale,and the explanatory variables included PD-related motor signs,rapid eye movement sleep behavior disorders,and neuropsychological tests.The support vector machine was used to develop a DPD prediction model.RESULTS When the effects of PD motor symptoms were compared using“functional weight”,late motor complications(occurrence of levodopa-induced dyskinesia)were the most influential risk factors for Parkinson's symptoms.CONCLUSION It is necessary to develop customized screening tests that can detect DPD in the early stage and continuously monitor high-risk groups based on the factors related to DPD derived from this predictive model in order to maintain the emotional health of PD patients. | Haewon Byeon | 2020 | World Journal of Psychiatry2020，10，10： | 5 |
| 2 | Unexpected Pulmonary Events during Endotracheal Intubation in a Pediatric Patient显示文摘 | Hue Jung Park Haewon Chung Min Soo Lee Hyun Jung Koh | 2017 | Chinese Medical Journal2017，，18： | 2 |
| 3 | Surfac- tant-enhanced ozone sparing for removal of organic com- pounds from sand 显示文摘 | Kim Heonki Yang Sukyeong ang Yang Haewon | 2013 | Journal of Environmental Science and Health Part A2013，48，5： | 1 |
| 4 | Carrier frequency offset compensation for uplink of OFDM-FDMA systems显示文摘 | CHOI Jihoon LEE Changoo JUNG Haewon | 2000 | IEEE Commun Lett2000，4，12： | 1 |
| 5 | Role of Plasmapheresis in the Management of Acute Hepatic Failure in Children显示文摘 | Andrew L. Singer Kim M. Olthoff Haewon Kim Elizabeth Rand Gideon Zamir Abraham Shaked | 2001 | Annals of Surgery2001，，3： | 1 |
| 6 | Bowel Wall Thickening in Patients with Crohn’s Disease: CT Patterns and Correlation with Inflammatory Activity显示文摘 | Dongil Choi Soon Jin Lee Young Ah Cho Hyo K Lim Seung Hoon Kim Won Jae Lee Jae Hoon Lim Haewon Park Young Rae Lee | 2003 | Clinical Radiology2003，，1： | 1 |
| 7 | From the wisdom of crowds to my own judgment in microfinance through online peer-to-peer lending platforms显示文摘 | Haewon Yum Byungtae Lee Myungsin Chae | 2012 | Electronic Commerce Research and Applications2012，，5： | 1 |
| 8 | From the wisdom of crowds to my own judgment in microfinance through online peer-to-peer lending platforms显示文摘 | Haewon Yum Byungtae Lee Myungsin Chae | 2012 | Electronic Commerce Research and Applications2012，，5： | 1 |
| 9 | Hydroxyapatite coating on titanium substrate with titania buffer layer processed by sol-gel method 显示文摘 | Kim Haewon Koh Younghag Li Longhao | 2004 | Biomaterials2004，25，13： | 1 |
| 10 | From the wisdom of crowds to my own judgment in microfinance through online peer-to-peer lending platforms显示文摘 | Haewon Yum Byungtae Lee Myungsin Chae | 2012 | Electronic Commerce Research and Applications2012，，5： | 1 |
| 11 | Im- proved biological performance of Ti implants due to sur- face modification by micro-arc oxidation显示文摘 | Li Longhao Kong Yongming Kim Haewon | 2004 | Biomaterials2004，25，14： | 1 |
| 12 | From the Wisdom of Crowds to My Own Judgment in Microfinance Through Online Peer-to- peer Lending Platforms显示文摘 | HAEWON YUM BYUNGTAE LEE MYUNGSIN CHAE | 2012 | Electronic Commerce Re- search and Applications2012，，5： | 1 |
| 13 | Predicting South Korea adolescents vulnerable to depressive disorder using Bayesian nomogram:A community-based crosssectional study显示文摘BACKGROUND Although South Korea has developed and carried out evidence-based interventions and prevention programs to prevent depressive disorder in adolescents,the number of adolescents with depressive disorder has increased every year for the past 10 years.AIM To develop a nomogram based on a naïve Bayesian algorithm by using epidemiological data on adolescents in South Korea and present baseline data for screening depressive disorder in adolescents.METHODS Epidemiological data from 2438 subjects who completed a brief symptom inventory questionnaire were used to develop a model based on a Bayesian nomogram for predicting depressive disorder in adolescents.RESULTS Physical symptoms,aggression,social withdrawal,attention,satisfaction with school life,mean sleeping hours,and conversation time with parents were influential factors on depressive disorder in adolescents.Among them,physical symptoms were the most influential.CONCLUSION Active intervention by periodically checking the emotional state of adolescents and offering individual counseling and in-depth psychological examinations when necessary are required to mitigate depressive disorder in adolescents. | Haewon Byeon | 2022 | World Journal of Psychiatry2022，12，7： | 1 |
| 14 | From the wisdom of crowds to my own judgment in microfinance through online peer-to-peer lending platforms显示文摘 | Haewon Yum Byungtae Lee Myungsin Chae | 2012 | Electronic Commerce Research and Applications2012，，5： | 1 |
| 15 | Guidelines on the use of therapeutic apheresis in clinical practice—Evidence‐based approach from the apheresis applications committee of the American Society for Apheresis显示文摘 | Zbigniew M.Szczepiorkowski Jeffrey L.Winters NicholasBandarenko Haewon C.Kim Michael L.Linenberger Marisa B.Marques RavindraSarode JosephSchwartz RobertWeinstein Beth H.Shaz | 2010 | J. Clin. Apheresis2010，，： | 1 |
| 16 | dom of Crowds to My Own Judgment in Microfinanee Through Online Peer-w-peer Lending Platforms显示文摘 | Haewon Yum Byungtae Lee Myungsin Chae From the Wis | 2012 | Electronic Com- merce Research and Appfications2012，，11： | 1 |
| 17 | A U.S.‒China coal power transition and the global 1.5℃ pathway显示文摘As the world seeks to increase ambition rapidly to limit global warming to 1.5℃,joint leadership from the world's largest greenhouse gas(GHG)emitters-the United States(U.S.)and China-will be critical to deliver significant emissions reductions from their own countries as well as to catalyze increased international action.After a period of uncertainty in international climate policy,these countries now both have current leadership that supports ambitious climate action.In this context,a feasible,high-impact,and potentially globally catalytic agreement by the U.S.and China to transition away from coal to clean energy would be a major contribution toward this global effort.We undertake a plant-by-plant assessment in the power sector to identify practical coal retirement pathways for each country that are in line with national priorities and the global 1.5℃ target.Our plant-by-plant analysis shows that the 1.5℃-compatible pathways may result in an average retirement age of 47 years for the U.S.coal plants and 22 years for Chinese coal plants,raising important questions of how to compare broader economic,employment,and social impacts.We also demonstrate that such pathways would also lead to significant emissions reductions,lowering overall global energy-related CO_(2) emissions by about 9%in 2030 relative to 2020.A catalytic effect from the possibility of other countries taking compatible actions is estimated to reduce global emissions by 5.1 Gt CO_(2) in 2030 and by 10.1 Gt CO_(2) in 2045. | Ryna Yiyun CUI Nathan HULTMAN Di-Yang CUI Haewon MCJEON Leon CLARKE Jia-Hai YUAN Wen-Jia CAI | 2022 | Advances in Climate Change Research2022，13，2： | 0 |
| 18 | Developing a nomogram for predicting the depression of senior citizens living alone while focusing on perceived social support显示文摘BACKGROUND Although the number of senior citizens living alone is increasing,only a few studies have identified factors related to the depression characteristics of senior citizens living alone by using epidemiological survey data that can represent a population group.AIM To evaluate prediction performance by building models for predicting the depression of senior citizens living alone that included subjective social isolation and perceived social support as well as personal characteristics such as age and drinking.METHODS This study analyzed 1558 senior citizens(695 males and 863 females)who were 60 years or older and completed an epidemiological survey representing the South Korean population.Depression,an outcome variable,was measured using the short form of the Korean version CES-D(short form of CES-D).RESULTS The prevalence of depression among the senior citizens living alone was 7.7%.The results of multiple logistic regression analysis showed that the experience of suicidal urge over the past year,subjective satisfaction with help from neighbors,subjective loneliness,age,and self-esteem were significantly related to the depression of senior citizens living alone(P<0.05).The results of 10-fold cross validation showed that the area under the curve of the nomogram was 0.96,and the F1 score of it was 0.97.CONCLUSION It is necessary to strengthen the social network of senior citizens living alone with friends and neighbors based on the results of this study to protect them from depression. | Haewon Byeon | 2021 | World Journal of Psychiatry2021，11，12： | 0 |
| 19 | Industry cluster,organizational diversity,and innovation显示文摘This study explains the factors that enhance the innovation performance of a cluster by focusing on its knowledge spillovers.Based on the literature on industry clusters,organizational diversity,and innovation,we suggest testable propositions.Specifically,this study suggests that two types of organizational diversity(diversity of nationality and organization type)positively impact the innovation performance of the cluster.In addition,the cluster network size and embeddedness have a positive moderating effect on the relationship between organizational diversity and innovation performance.This study aims to determine whether the innovation performance of industry clusters varies depending on the degree of diversity of organizations in the cluster and whether their network characteristics may strengthen the positive effect of organizational diversity.This study contributes to the research stream related to industry clusters and organizational diversity and provides practical implications to practitioners participating in creating and growing such clusters. | Haewon Kim Seung-June Hwang Woojin Yoon | 2023 | International Journal of Innovation Studies2023，7，3： | 0 |
| 20 | Block Incremental Dense Tucker Decomposition with Application to Spatial and Temporal Analysis of Air Quality Data显示文摘How can we efficiently store and mine dynamically generated dense tensors for modeling the behavior of multidimensional dynamic data?Much of the multidimensional dynamic data in the real world is generated in the form of time-growing tensors.For example,air quality tensor data consists of multiple sensory values gathered from wide locations for a long time.Such data,accumulated over time,is redundant and consumes a lot ofmemory in its raw form.We need a way to efficiently store dynamically generated tensor data that increase over time and to model their behavior on demand between arbitrary time blocks.To this end,we propose a Block IncrementalDense Tucker Decomposition(BID-Tucker)method for efficient storage and on-demand modeling ofmultidimensional spatiotemporal data.Assuming that tensors come in unit blocks where only the time domain changes,our proposed BID-Tucker first slices the blocks into matrices and decomposes them via singular value decomposition(SVD).The SVDs of the time×space sliced matrices are stored instead of the raw tensor blocks to save space.When modeling from data is required at particular time blocks,the SVDs of corresponding time blocks are retrieved and incremented to be used for Tucker decomposition.The factor matrices and core tensor of the decomposed results can then be used for further data analysis.We compared our proposed BID-Tucker with D-Tucker,which our method extends,and vanilla Tucker decomposition.We show that our BID-Tucker is faster than both D-Tucker and vanilla Tucker decomposition and uses less memory for storage with a comparable reconstruction error.We applied our proposed BID-Tucker to model the spatial and temporal trends of air quality data collected in South Korea from 2018 to 2022.We were able to model the spatial and temporal air quality trends.We were also able to verify unusual events,such as chronic ozone alerts and large fire events. | SangSeok Lee HaeWon Moon Lee Sael | 2024 | Computer Modeling in Engineering & Sciences2024，139，4： | 0 |
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