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1 Identification of Sleep Apnea Severity Based on Deep Learning from a Short-term Normal ECG
Erdenebayar Urtnasan, Jong-Uk Park, Eun Yeon Joo, Kyoung Joung Lee
J Korean Med Sci.2020;35(47):e399.  Published online 2020 November 11     DOI: http://dx.doi.org/10.3346/jkms.2020.35.e399
2 Distribution and Characteristics of Pancreatic Volume Using Computed Tomography Volumetry
Jihyun Yoon, Kwang Gi Kim, Young Jae Kim, Sangheon Lim, Yeon-Ho Park, Doojin Kim, Hee-Taik Kang, Doo-Ho Lee
Healthc Inform Res.2020;26(4):321-327.   Published online 2020 October 31     DOI: http://dx.doi.org/10.4258/hir.2020.26.4.321
3 Machine Learning Application in Diabetes and Endocrine Disorders
Namki Hong, Heajeong Park, Yumie Rhee
J Korean Diabetes.2020;21(3):130-139.   Published online 2020 September 30     DOI: http://dx.doi.org/10.4093/jkd.2020.21.3.130
4 Nuclear Medicine Physics: Review of Advanced Technology
Jungsu S. Oh
Prog Med Phys.2020;31(3):81-89.   Published online 2020 September 30     DOI: http://dx.doi.org/10.14316/pmp.2020.31.3.81
5 Deep Learning in Radiation Oncology
Wonjoong Cheon, Haksoo Kim, Jinsung Kim
Prog Med Phys.2020;31(3):111-123.   Published online 2020 September 30     DOI: http://dx.doi.org/10.14316/pmp.2020.31.3.111
6 Analysis of Adverse Drug Reactions Identified in Nursing Notes Using Reinforcement Learning
Eunjoo Jeon, Youngsam Kim, Hojun Park, Rae Woong Park, Hyopil Shin, Hyeoun-Ae Park
Healthc Inform Res.2020;26(2):104-111.   Published online 2020 April 30     DOI: http://dx.doi.org/10.4258/hir.2020.26.2.104
7 Deep Learning in Upper Gastrointestinal Disorders: Status and Future Perspectives
Chang Seok Bang
Korean J Gastroenterol.2020;75(3):120-131.   Published online 2020 March 25     DOI: http://dx.doi.org/10.4166/kjg.2020.75.3.120
8 Machine Learning Applications in Endocrinology and Metabolism Research: An Overview
Namki Hong, Heajeong Park, Yumie Rhee
Endocrinol Metab.2020;35(1):71-84.   Published online 2020 March 19     DOI: http://dx.doi.org/10.3803/EnM.2020.35.1.71
9 Artificial intelligence, machine learning, and deep learning in women’s health nursing
Geum Hee Jeong
Korean J Women Health Nurs.2020;26(1):5-9.   Published online 2020 March 17     DOI: http://dx.doi.org/10.4069/kjwhn.2020.03.11
10 Radiomics and Deep Learning: Hepatic Applications
Hyo Jung Park, Bumwoo Park, Seung Soo Lee
Korean J Radiol.2020;21(4):387-401.   Published online 2020 March 4     DOI: http://dx.doi.org/10.3348/kjr.2019.0752
11 Low-Dose Abdominal CT Using a Deep Learning-Based Denoising Algorithm: A Comparison with CT Reconstructed with Filtered Back Projection or Iterative Reconstruction Algorithm
Yoon Joo Shin, Won Chang, Jong Chul Ye, Eunhee Kang, Dong Yul Oh, Yoon Jin Lee, Ji Hoon Park, Young Hoon Kim
Korean J Radiol.2020;21(3):356-364.   Published online 2020 February 11     DOI: http://dx.doi.org/10.3348/kjr.2019.0413
12 Machine Learning and Initial Nursing Assessment-Based Triage System for Emergency Department
Jae Yong Yu, Gab Yong Jeong, Ok Soon Jeong, Dong Kyung Chang, Won Chul Cha
Healthc Inform Res.2020;26(1):13-19.   Published online 2020 January 31     DOI: http://dx.doi.org/10.4258/hir.2020.26.1.13
13 Web-Based Spine Segmentation Using Deep Learning in Computed Tomography Images
Young Jae Kim, Bilegt Ganbold, Kwang Gi Kim
Healthc Inform Res.2020;26(1):61-67.   Published online 2020 January 31     DOI: http://dx.doi.org/10.4258/hir.2020.26.1.61
14 Possibility of predicting missing teeth using deep learning: a pilot study
Seon-Jip Kim, Dohyoung Rim, Jeong Uk Heo, Hyun-Jae Cho
J Korean Acad Oral Health.2019;43(4):210-216.   Published online 2019 December 26     DOI: http://dx.doi.org/10.11149/jkaoh.2019.43.4.210
15 Medical Big Data Is Not Yet Available: Why We Need Realism Rather than Exaggeration
Hun-Sung Kim, Dai-Jin Kim, Kun-Ho Yoon
Endocrinol Metab.2019;34(4):349-354.   Published online 2019 December 23     DOI: http://dx.doi.org/10.3803/EnM.2019.34.4.349
16 Development and Validation of a Deep Learning System for Segmentation of Abdominal Muscle and Fat on Computed Tomography
Hyo Jung Park, Yongbin Shin, Jisuk Park, Hyosang Kim, In Seob Lee, Dong-Woo Seo, Jimi Huh, Tae Young Lee, TaeYong Park, Jeongjin Lee, Kyung Won Kim
Korean J Radiol.2020;21(1):88-100.   Published online 2019 December 16     DOI: http://dx.doi.org/10.3348/kjr.2019.0470
17 Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning
Synho Do, Kyoung Doo Song, Joo Won Chung
Korean J Radiol.2020;21(1):33-41.   Published online 2019 December 6     DOI: http://dx.doi.org/10.3348/kjr.2019.0312
18 Augmentation of Doppler Radar Data Using Generative Adversarial Network for Human Motion Analysis
Ibrahim Alnujaim, Youngwook Kim
Healthc Inform Res.2019;25(4):344-349.   Published online 2019 October 31     DOI: http://dx.doi.org/10.4258/hir.2019.25.4.344
19 Deep Neural Network-Based Concentration Model for Oak Pollen Allergy Warning in South Korea
Yun Am Seo, Kyu Rang Kim, Changbum Cho, Jae-Won Oh, Tae Hee Kim
Allergy Asthma Immunol Res.2020;12(1):149-163.   Published online 2019 October 7     DOI: http://dx.doi.org/10.4168/aair.2020.12.1.149
20 Deep Learning Algorithm for Reducing CT Slice Thickness: Effect on Reproducibility of Radiomic Features in Lung Cancer
Sohee Park, Sang Min Lee, Kyung-Hyun Do, June-Goo Lee, Woong Bae, Hyunho Park, Kyu-Hwan Jung, Joon Beom Seo
Korean J Radiol.2019;20(10):1431-1440.   Published online 2019 August 27     DOI: http://dx.doi.org/10.3348/kjr.2019.0212

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