2.Eosinophilic Cholangitis Diagnosed in a Patient with Abnormal Liver Enzymes: A Case Report
Sung Hoon CHANG ; Jun Yeol KIM ; Yong Soo SONG ; Tae Seung LEE ; Jin Ho CHOI ; Woo Hyun PAIK ; Sang Hyub LEE ; Ji Kon RYU ; In Rae CHO
Korean Journal of Pancreas and Biliary Tract 2025;30(1):19-25
It is difficult to determine a cause of bile duct stricture and dilatation. Eosinophilic cholangitis, a rare benign condition, may be one cause of bile duct stricture and dilatation. It can be evaluated using various methods of histopathology, radiographs, endoscopy, and hematologic findings. Treatment generally involves steroid therapy which can lead to improvement. This case report will discuss eosinophilic cholangitis, emphasizing that while it can easily be overlooked but should be considered in differential diagnoses.
3.Machine Learning Prediction of Attachment Type From Bio-Psychological Factors in Patients With Depression
Yoon Jae CHO ; Jin Sun RYU ; Jeong-Ho SEOK ; Eunjoo KIM ; Jooyoung OH ; Byung-Hoon KIM
Psychiatry Investigation 2025;22(4):412-423
Objective:
Adult attachment style is linked to how an individual responds to threats or stress and is known to be related to the onset of psychiatric symptoms such as depression. However, as the current assessment of attachment type mainly relies on self-report questionnaires and can be prone to bias, there is a need to incorporate physiological factors along with psychological symptoms and history in this process. We aimed to predict the measurement of two important types of adult attachment with heart rate variability (HRV), early life stress experience, and subjective psychiatric symptoms.
Methods:
Five hundred eighty-two subjects with depressive disorder were recruited retrospectively from January 2015 to June 2021. The experience of early life stress and psychiatric symptoms were collected, and HRV measures were obtained as input for an ensembled Voting Regressor model of machine learning-based regression models, including linear regression, ElasticNet, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost).
Results:
Model performances evaluated with R-squared score averaged across 30 seeds were 0.377 and 0.188 for anxious- and avoidant-attachment, respectively. Mean absolute error averaged to 13.251 and 12.083, respectively. Shapley value importance analysis indicated that for both attachment types, the most important feature was the trait-anxiety, followed by emotional abuse, state-anxiety or self-reported depressive symptoms, and fear or helplessness felt in the moment of an early life stressor.
Conclusion
Our results provide the evidence base that may be utilized in clinical settings to predict the degree of attachment type using bio-psychological factors.
4.The Cancer Clinical Library Database (CCLD) from the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) Project
Sangwon LEE ; Yeon Ho CHOI ; Hak Min KIM ; Min Ah HONG ; Phillip PARK ; In Hae KWAK ; Ye Ji KANG ; Kui Son CHOI ; Hyun-Joo KONG ; Hyosung CHA ; Hyun-Jin KIM ; Kwang Sun RYU ; Young Sang JEON ; Hwanhee KIM ; Jip Min JUNG ; Jeong-Soo IM ; Heejung CHAE
Cancer Research and Treatment 2025;57(1):19-27
The common data model (CDM) has found widespread application in healthcare studies, but its utilization in cancer research has been limited. This article describes the development and implementation strategy for Cancer Clinical Library Databases (CCLDs), which are standardized cancer-specific databases established under the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) project by the Korean Ministry of Health and Welfare. Fifteen leading hospitals and fourteen academic associations in Korea are engaged in constructing CCLDs for 10 primary cancer types. For each cancer type-specific CCLD, cancer data experts determine key clinical data items essential for cancer research, standardize these items across cancer types, and create a standardized schema. Comprehensive clinical records covering diagnosis, treatment, and outcomes, with annual updates, are collected for each cancer patient in the target population, and quality control is based on six-sigma standards. To protect patient privacy, CCLDs follow stringent data security guidelines by pseudonymizing personal identification information and operating within a closed analysis environment. Researchers can apply for access to CCLD data through the K-CURE portal, which is subject to Institutional Review Board and Data Review Board approval. The CCLD is considered a pioneering standardized cancer-specific database, significantly representing Korea’s cancer data. It is expected to overcome limitations of previous CDMs and provide a valuable resource for multicenter cancer research in Korea.
6.Eosinophilic Cholangitis Diagnosed in a Patient with Abnormal Liver Enzymes: A Case Report
Sung Hoon CHANG ; Jun Yeol KIM ; Yong Soo SONG ; Tae Seung LEE ; Jin Ho CHOI ; Woo Hyun PAIK ; Sang Hyub LEE ; Ji Kon RYU ; In Rae CHO
Korean Journal of Pancreas and Biliary Tract 2025;30(1):19-25
It is difficult to determine a cause of bile duct stricture and dilatation. Eosinophilic cholangitis, a rare benign condition, may be one cause of bile duct stricture and dilatation. It can be evaluated using various methods of histopathology, radiographs, endoscopy, and hematologic findings. Treatment generally involves steroid therapy which can lead to improvement. This case report will discuss eosinophilic cholangitis, emphasizing that while it can easily be overlooked but should be considered in differential diagnoses.
7.Machine Learning Prediction of Attachment Type From Bio-Psychological Factors in Patients With Depression
Yoon Jae CHO ; Jin Sun RYU ; Jeong-Ho SEOK ; Eunjoo KIM ; Jooyoung OH ; Byung-Hoon KIM
Psychiatry Investigation 2025;22(4):412-423
Objective:
Adult attachment style is linked to how an individual responds to threats or stress and is known to be related to the onset of psychiatric symptoms such as depression. However, as the current assessment of attachment type mainly relies on self-report questionnaires and can be prone to bias, there is a need to incorporate physiological factors along with psychological symptoms and history in this process. We aimed to predict the measurement of two important types of adult attachment with heart rate variability (HRV), early life stress experience, and subjective psychiatric symptoms.
Methods:
Five hundred eighty-two subjects with depressive disorder were recruited retrospectively from January 2015 to June 2021. The experience of early life stress and psychiatric symptoms were collected, and HRV measures were obtained as input for an ensembled Voting Regressor model of machine learning-based regression models, including linear regression, ElasticNet, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost).
Results:
Model performances evaluated with R-squared score averaged across 30 seeds were 0.377 and 0.188 for anxious- and avoidant-attachment, respectively. Mean absolute error averaged to 13.251 and 12.083, respectively. Shapley value importance analysis indicated that for both attachment types, the most important feature was the trait-anxiety, followed by emotional abuse, state-anxiety or self-reported depressive symptoms, and fear or helplessness felt in the moment of an early life stressor.
Conclusion
Our results provide the evidence base that may be utilized in clinical settings to predict the degree of attachment type using bio-psychological factors.
9.Eosinophilic Cholangitis Diagnosed in a Patient with Abnormal Liver Enzymes: A Case Report
Sung Hoon CHANG ; Jun Yeol KIM ; Yong Soo SONG ; Tae Seung LEE ; Jin Ho CHOI ; Woo Hyun PAIK ; Sang Hyub LEE ; Ji Kon RYU ; In Rae CHO
Korean Journal of Pancreas and Biliary Tract 2025;30(1):19-25
It is difficult to determine a cause of bile duct stricture and dilatation. Eosinophilic cholangitis, a rare benign condition, may be one cause of bile duct stricture and dilatation. It can be evaluated using various methods of histopathology, radiographs, endoscopy, and hematologic findings. Treatment generally involves steroid therapy which can lead to improvement. This case report will discuss eosinophilic cholangitis, emphasizing that while it can easily be overlooked but should be considered in differential diagnoses.
10.Machine Learning Prediction of Attachment Type From Bio-Psychological Factors in Patients With Depression
Yoon Jae CHO ; Jin Sun RYU ; Jeong-Ho SEOK ; Eunjoo KIM ; Jooyoung OH ; Byung-Hoon KIM
Psychiatry Investigation 2025;22(4):412-423
Objective:
Adult attachment style is linked to how an individual responds to threats or stress and is known to be related to the onset of psychiatric symptoms such as depression. However, as the current assessment of attachment type mainly relies on self-report questionnaires and can be prone to bias, there is a need to incorporate physiological factors along with psychological symptoms and history in this process. We aimed to predict the measurement of two important types of adult attachment with heart rate variability (HRV), early life stress experience, and subjective psychiatric symptoms.
Methods:
Five hundred eighty-two subjects with depressive disorder were recruited retrospectively from January 2015 to June 2021. The experience of early life stress and psychiatric symptoms were collected, and HRV measures were obtained as input for an ensembled Voting Regressor model of machine learning-based regression models, including linear regression, ElasticNet, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost).
Results:
Model performances evaluated with R-squared score averaged across 30 seeds were 0.377 and 0.188 for anxious- and avoidant-attachment, respectively. Mean absolute error averaged to 13.251 and 12.083, respectively. Shapley value importance analysis indicated that for both attachment types, the most important feature was the trait-anxiety, followed by emotional abuse, state-anxiety or self-reported depressive symptoms, and fear or helplessness felt in the moment of an early life stressor.
Conclusion
Our results provide the evidence base that may be utilized in clinical settings to predict the degree of attachment type using bio-psychological factors.

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