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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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Effects of Emotional Intelligence, Multicultural Perception on Cultural Competence in Nursing Students

Hye Ri N

BACKGROUND: The purpose of this study was to investigate the influence of emotional intelligence and multi-cultural perception on the cultural competence of nursing students. METHODS: A Participants consisted of 211 registered...
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How Will the Digital Tools Change Healthcare?

Kim C

Digital technology has transformed our lives. Healthcare is not an exception. Many devices have showed up in various areas of healthcare to offer new value. The first area affected is...
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National Lung Cancer Screening Program in Korea: More Harm Than Good

Shin SW, Lee J

Although the result of low dose computed tomography (LDCT) screening for high risk smoker for lung cancer (National Lung Screening Trial, NLST) showed 20% of lower lung cancer death compare...
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Internet of Things, Digital Biomarker, and Artificial Intelligence in Spine: Current and Future Perspectives

Nam KH, Kim DH, Choi BK, Han IH

Recent interest in medical artificial intelligence (AI) has increased with onset of the fourth industrial revolution. Real-time monitoring of patients is an important research area of medical AI. The medical...
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Commentary on An Application of Artificial Intelligence to Diagnostic Imaging of Spine Disease: Estimating Spinal Alignment From Moiré Images

Cheung KM

No abstract available.
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An Application of Artificial Intelligence to Diagnostic Imaging of Spine Disease: Estimating Spinal Alignment From Moiré Images

Watanabe K, Aoki Y, Matsumoto

The use of artificial intelligence (AI) as a tool supporting the diagnosis and treatment of spinal diseases is eagerly anticipated. In the field of diagnostic imaging, the possible application of...
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Commentary: Artificial Intelligence for Adult Spinal Deformity

Lenke LG

No abstract available.
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Artificial Intelligence for Adult Spinal Deformity

Joshi RS, Haddad AF, Lau D, Ames CP

Adult spinal deformity (ASD) is a complex disease that significantly affects the lives of many patients. Surgical correction has proven to be effective in achieving improvement of spinopelvic parameters as...
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Predictive Analytics in Spine Oncology Research: First Steps, Limitations, and Future Directions

Massaad E, Fatima N, Hadzipasic M, Alvarez-Breckenridge C, Shankar GM, Shin JH

The potential of big data analytics to improve the quality of care for patients with spine tumors is significant. At this moment, the application of big data analytics to oncology...
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Deep Learning in Medical Imaging

Kim M, Yun J, Cho Y, Shin K, Jang R, Bae HJ, Kim N

The artificial neural network (ANN), one of the machine learning (ML) algorithms, inspired by the human brain system, was developed by connecting layers with artificial neurons. However, due to the...
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Applications of Machine Learning Using Electronic Medical Records in Spine Surgery

Schwartz J, Gao M, Geng EA, Mody KS, Mikhail CM, Cho SK

Developments in machine learning in recent years have precipitated a surge in research on the applications of artificial intelligence within medicine. Machine learning algorithms are beginning to impact medicine broadly,...
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Artificial Intelligence in Neurosurgery: A Comment on the Possibilities

Perez-Breva L, Shin JH

No abstract available.
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