- Radiomics and Deep Learning: Hepatic Applications
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Park HJ, Park B, Lee SS
- KMID: 2471805
- Korean J Radiol.
- 2020 Apr;21(4):387-401.
- doi: 10.3348/kjr.2019.0752
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
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Bang CS
- KMID: 2471895
- Korean J Gastroenterol.
- 2020 Mar;75(3):120-131.
- doi: 10.4166/kjg.2020.75.3.120
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
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Hong N, Park H, Rhee Y
- KMID: 2471722
- Endocrinol Metab.
- 2020 Mar;35(1):71-84.
- doi: 10.3803/EnM.2020.35.1.71
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
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Park HJ, Shin Y, Park J, Kim H, Lee IS, Seo DW, Huh J, Lee TY, Park T, Lee J, Kim KW
- KMID: 2467045
- Korean J Radiol.
- 2020 Jan;21(1):88-100.
- doi: 10.3348/kjr.2019.0470
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
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Do S, Song KD, Chung JW
- KMID: 2467040
- Korean J Radiol.
- 2020 Jan;21(1):33-41.
- doi: 10.3348/kjr.2019.0312
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
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Kim HS, Kim EK, Park HK, Ahn DH, Kim MJ, Lee HJ
- KMID: 2466581
- J Korean Med Sci.
- 2020 Jan;35(1):e4.
- doi: 10.3346/jkms.2020.35.e4
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?
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Kim HS
- KMID: 2466578
- J Korean Med Sci.
- 2020 Jan;35(1):e1.
- doi: 10.3346/jkms.2020.35.e1
No abstract available. -
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- Development and External Validation of a Deep Learning Algorithm for Prognostication of Cardiovascular Outcomes
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Cho IJ, Sung JM, Kim HC, Lee SE, Chae MH, Kavousi M, Rueda-Ochoa OL, Ikram MA, Franco OH, Min JK, Chang HJ
- KMID: 2465666
- Korean Circ J.
- 2020 Jan;50(1):72-84.
- doi: 10.4070/kcj.2019.0105
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
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Hye Ri N
- KMID: 2470618
- Health Commun.
- 2019 Dec;14(2):125-131.
- doi: 10.15715/kjhcom.2019.14.2.125
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?
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Kim C
- KMID: 2470425
- J Sleep Med.
- 2019 Dec;16(2):71-74.
- doi: 10.13078/jsm.190040
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
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Shin SW, Lee J
- KMID: 2469163
- Korean J Health Promot.
- 2019 Dec;19(4):166-170.
- doi: 10.15384/kjhp.2019.19.4.166
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
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Nam KH, Kim DH, Choi BK, Han IH
- KMID: 2469046
- Neurospine.
- 2019 Dec;16(4):705-711.
- doi: 10.14245/ns.1938388.194
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
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Cheung KM
- KMID: 2469045
- Neurospine.
- 2019 Dec;16(4):703-704.
- doi: 10.14245/ns.1938438.219
No abstract available. -
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- An Application of Artificial Intelligence to Diagnostic Imaging of Spine Disease: Estimating Spinal Alignment From Moiré Images
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Watanabe K, Aoki Y, Matsumoto
- KMID: 2469044
- Neurospine.
- 2019 Dec;16(4):697-702.
- doi: 10.14245/ns.1938426.213
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
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Lenke LG
- KMID: 2469043
- Neurospine.
- 2019 Dec;16(4):695-696.
- doi: 10.14245/ns.19edi.020
No abstract available. -
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- Artificial Intelligence for Adult Spinal Deformity
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Joshi RS, Haddad AF, Lau D, Ames CP
- KMID: 2469042
- Neurospine.
- 2019 Dec;16(4):686-694.
- doi: 10.14245/ns.1938414.207
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
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Massaad E, Fatima N, Hadzipasic M, Alvarez-Breckenridge C, Shankar GM, Shin JH
- KMID: 2469040
- Neurospine.
- 2019 Dec;16(4):669-677.
- doi: 10.14245/ns.1938402.201
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
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Kim M, Yun J, Cho Y, Shin K, Jang R, Bae HJ, Kim N
- KMID: 2469039
- Neurospine.
- 2019 Dec;16(4):657-668.
- doi: 10.14245/ns.1938396.198
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
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Schwartz J, Gao M, Geng EA, Mody KS, Mikhail CM, Cho SK
- KMID: 2469037
- Neurospine.
- 2019 Dec;16(4):643-653.
- doi: 10.14245/ns.1938386.193
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
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Perez-Breva L, Shin JH
- KMID: 2469036
- Neurospine.
- 2019 Dec;16(4):640-642.
- doi: 10.14245/ns.1938404.202
No abstract available. -
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