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Radiomics and Deep Learning: Hepatic Applications

Park HJ, Park B, Lee SS

Radiomics and deep learning have recently gained attention in the imaging assessment of various liver diseases. Recent research has demonstrated the potential utility of radiomics and deep learning in staging...
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Deep Learning in Upper Gastrointestinal Disorders: Status and Future Perspectives

Bang CS

Artificial intelligence using deep learning has been applied to gastrointestinal disorders for the detection, classification, and delineation of various lesion images. With the accumulation of enormous medical records, the evolution...
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Machine Learning Applications in Endocrinology and Metabolism Research: An Overview

Hong N, Park H, Rhee Y

Machine learning (ML) applications have received extensive attention in endocrinology research during the last decade. This review summarizes the basic concepts of ML and certain research topics in endocrinology and...
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Development and Validation of a Deep Learning System for Segmentation of Abdominal Muscle and Fat on Computed Tomography

Park HJ, Shin Y, Park J, Kim H, Lee IS, Seo DW, Huh J, Lee TY, Park T, Lee J, Kim KW

OBJECTIVE: We aimed to develop and validate a deep learning system for fully automated segmentation of abdominal muscle and fat areas on computed tomography (CT) images. MATERIALS AND METHODS: A fully...
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Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning

Do S, Song KD, Chung JW

Artificial intelligence has been applied to many industries, including medicine. Among the various techniques in artificial intelligence, deep learning has attained the highest popularity in medical imaging in recent years....
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Cognitive Outcomes of Children with Very Low Birth Weight at 3 to 5 Years of Age

Kim HS, Kim EK, Park HK, Ahn DH, Kim MJ, Lee HJ

BACKGROUND: The cognitive consequences and risk factors based long-term outcome of very-low-birth-weight (VLBW; < 1,500 g) infants in Korea has not been studied. The aim of this study was to...
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Decision-Making in Artificial Intelligence: Is It Always Correct?

Kim HS

No abstract available.
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Development and External Validation of a Deep Learning Algorithm for Prognostication of Cardiovascular Outcomes

Cho IJ, Sung JM, Kim HC, Lee SE, Chae MH, Kavousi M, Rueda-Ochoa OL, Ikram MA, Franco OH, Min JK, Chang HJ

BACKGROUND AND OBJECTIVES: We aim to explore the additional discriminative accuracy of a deep learning (DL) algorithm using repeated-measures data for identifying people at high risk for cardiovascular disease (CVD),...
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The Prospect of a New Smart Healthcare System: A Wearable Device-Based Complex Structure of Position Detecting and Location Recognition System

Chung KJ, Kim J, Whangbo TK, Kim KH

In upcoming fourth industrial revolution era, it is inevitable to address smart healthcare as not only scientist but also clinician. We have the task to plan and realize this through...
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Epigenetics and Depression: An Update

Lin E, Tsai SJ

OBJECTIVE: Depression is associated with various environmental risk factors such as stress, childhood maltreatment experiences, and stressful life events. Current approaches to assess the pathophysiology of depression, such as epigenetics...
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Application of Artificial Intelligence in Lung Cancer Screening

Lee SM, Park CM

Lung cancer is a leading cause of deaths due to cancer, worldwide. At present, low-dose computed tomography (CT) is the only established screening method for reducing lung cancer mortality. However,...
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Artificial intelligence in drug development: clinical pharmacologist perspective

Jang IJ

No abstract available.
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Relative Age Effects in Korean Football: Analysis of Age-Specific International Teams

Jeong TS, Bang SY, Park S, Lee YS, Kim YR, Kim YS

PURPOSE: This study aimed to identify relative age effects of South Korea national male football teams that participated in 38 international competitions in age-specific categories from 2000 to 2018; U-16...
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Current status and future direction of digital health in Korea

Shin SY

Recently, digital health has gained the attention of physicians, patients, and healthcare industries. Digital health, a broad umbrella term, can be defined as an emerging health area that uses brand...
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Clinical Usefulness of the Korean Developmental Screening Test (K-DST) for Developmental Delays

Jang CH, Kim SW, Jeon HR, Jung DW, Cho HE, Kim J, Lee JW

OBJECTIVE: To evaluate the clinical usefulness of the Korean Developmental Screening Test (K-DST) via comparison with Korean Ages and Stages Questionnaire (K-ASQ) for the diagnosis of developmental delay in pediatric...
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Factors Affecting Clinical Practicum Stress of Nursing Students: Using the Lazarus and Folkman's Stress-Coping Model

Kim SH, Lee J, Jang M

PURPOSE: This study was conducted to test a path model for the factors related to undergraduate nursing students' clinical practicum stress, based on Lazarus and Folkman's stress-coping model. METHODS: This study...
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Emotional Intelligence, Problem Solving Ability, Self Efficacy, and Clinical Performance among Nursing Students: A Structural Equation Model

Kim MS, Sohn SK

PURPOSE: This study aimed to construct and test the structural relationships between self efficacy and clinical performance among undergraduate nursing students. The model was based on Bandura's self efficacy theory...
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Machine Learning Model to Predict Osteoporotic Spine with Hounsfield Units on Lumbar Computed Tomography

Nam KH, Seo I, Kim DH, Lee JI, Choi BK, Han IH

OBJECTIVE: Bone mineral density (BMD) is an important consideration during fusion surgery. Although dual X-ray absorptiometry is considered as the gold standard for assessing BMD, quantitative computed tomography (QCT) provides...
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Overview of Deep Learning in Gastrointestinal Endoscopy

Min JK, Kwak MS, Cha JM

Artificial intelligence is likely to perform several roles currently performed by humans, and the adoption of artificial intelligence-based medicine in gastroenterology practice is expected in the near future. Medical image-based...
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AI in Medicine: Need of Orchestration for High-Performance

Choi J

No abstract available.
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