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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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Effects of Reading a Free Electronic Book on Regional Anatomy with Schematics and Mnemonics on Student Learning

Chung BS, Koh KS, Oh CS, Park JS, Lee JH, Chung MS

BACKGROUND: To help medical students learn anatomy effectively in limited hours, a regional anatomy book enhancing students' memorization was developed. METHODS: Only anatomical terms essential for basic cadaver dissection are included...
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Web-Based Spine Segmentation Using Deep Learning in Computed Tomography Images

Kim YJ, Ganbold B, Kim KG

OBJECTIVES: Back pain, especially lower back pain, is experienced in 60% to 80% of adults at some points during their lives. Various studies have found that lower back pain is...
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Prediction of Chronic Disease-Related Inpatient Prolonged Length of Stay Using Machine Learning Algorithms

Symum H, Zayas-Castro JL

OBJECTIVES: The study aimed to develop and compare predictive models based on supervised machine learning algorithms for predicting the prolonged length of stay (LOS) of hospitalized patients diagnosed with five...
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Machine Learning and Initial Nursing Assessment-Based Triage System for Emergency Department

Yu JY, Jeong GY, Jeong OS, Chang DK, Cha WC

OBJECTIVES: The aim of this study was to develop machine learning (ML) and initial nursing assessment (INA)-based emergency department (ED) triage to predict adverse clinical outcome. METHODS: The retrospective study included...
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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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Feasibility of fully automated classification of whole slide images based on deep learning

Cho KO, Lee SH, Jang HJ

Although microscopic analysis of tissue slides has been the basis for disease diagnosis for decades, intra- and inter-observer variabilities remain issues to be resolved. The recent introduction of digital scanners...
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Machine Learning: a New Opportunity for Risk Prediction

Kwon O, Na W, Kim YH

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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Deep learning for stage prediction in neuroblastoma using gene expression data

Park A, Nam S

Neuroblastoma is a major cause of cancer death in early childhood, and its timely and correct diagnosis is critical. Gene expression datasets have recently been considered as a powerful tool...
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Effects of a 3D Visualization Application and Game-Based Learning on Gross Anatomy Education: Focused on Some Students in the Department of Dental Hygiene

Kim DH

There is a lack of domestic studies that have designed anatomical education programs for systematic cadaver dissection and compared them with existing teaching methods. The purpose of this study was...
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Radiomics MRI Phenotyping with Machine Learning to Predict the Grade of Lower-Grade Gliomas: A Study Focused on Nonenhancing Tumors

Park YW, Choi YS, Ahn SS, Chang JH, Kim SH, Lee SK

OBJECTIVE: To assess whether radiomics features derived from multiparametric MRI can predict the tumor grade of lower-grade gliomas (LGGs; World Health Organization grade II and grade III) and the nonenhancing...
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Motor Skill Learning on the Ipsi-Lateral Upper Extremity to the Damaged Hemisphere in Stroke Patients

Son SM, Hwang YT, Nam SH, Kwon Y

PURPOSE: This study examined whether there is a difference in motor learning through short-term repetitive movement practice in stroke survivors with a unilateral brain injury compared to normal elderly participants. METHODS:...
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Spatial Learning and Motor Deficits in Vacuolar Protein Sorting-associated Protein 13b (Vps13b) Mutant Mouse

Kim MJ, Lee RU, Oh J, Choi JE, Kim H, Lee K, Hwang SK, Lee JH, Lee JA, Kaang BK, Lim CS, Lee YS

Vacuolar protein sorting-associated protein 13B (VPS13B), also known as COH1, is one of the VPS13 family members which is involved in transmembrane transport, Golgi integrity, and neuritogenesis. Mutations in the...
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Differences between Perceived Readiness for Interprofessional Learning in Nursing and Other Health-related Students

Lee H, Kim IS, Lee TW, Kim GS, Cho E, Lee KH, Kim J

PURPOSE: The purpose of this study was to investigate the level of perceived readiness for interprofessional learning and its differences between nursing and other health-related students. Methods METHODS: A web-based survey...
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Learning Experience of Undergraduate Nursing Students in Simulation: A Meta-synthesis and Meta-ethnography Study

Lee J, Jeon J, Kim S

PURPOSE: The purpose of this study was to review and synthesize the existing literature on the experience of nursing students in simulation. METHODS: A systematic review was undertaken using meta-ethnography. Eight...
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Effects of Team-based Learning using Concept Mapping on Critical Thinking Disposition and Metacognition of Nursing Students

Jeong YW, Min HY

PURPOSE: This study aimed to examine the effects of team-based learning using concept mapping on critical thinking disposition and metacognition on college of nursing students. METHODS: A non-equivalent control group pretest-posttest...
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