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| 1 |
Artificial Intelligence in Point-of-Care Testing
Adil I. Khan, Mazeeya Khan, Raheeb Khan
Ann Lab Med.2023;43(5):401-407. Published online 2023 April 21
DOI: http://dx.doi.org/10.3343/alm.2023.43.5.401
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| 2 |
Convolutional neural network of age-related trends digital radiographs of medial clavicle in a Thai population: a preliminary study
Phisamon Kengkard, Jirachaya Choovuthayakorn, Chollada Mahakkanukrauh, Nadee Chitapanarux, Pittayarat Intasuwan, Yanumart Malatong, Apichat Sinthubua, Patison Palee, Sakarat Na Lampang, Pasuk Mahakkanukrauh
Anat Cell Biol.2023;56(1):86-93. Published online 2023 March 31
DOI: http://dx.doi.org/10.5115/acb.22.205
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| 3 |
Deep learning algorithms for identifying 79 dental implant types
Hyun-Jun Kong, Jin-Yong Yoo, Sang-Ho Eom, Jun-Hyeok Lee
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| 4 |
Efficient Segmentation for Left Atrium With Convolution Neural Network Based on Active Learning in Late Gadolinium Enhancement Magnetic Resonance Imaging
Yongwon Cho, Hyungjoon Cho, Jaemin Shim, Jong-Il Choi, Young-Hoon Kim, Namkug Kim, Yu-Whan Oh, Sung Ho Hwang
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| 5 |
Accuracy of artificial intelligence-assisted landmark identification in serial lateral cephalograms of Class III patients who underwent orthodontic treatment and two-jaw orthognathic surgery
Mihee Hong, Inhwan Kim, Jin-Hyoung Cho, Kyung-Hwa Kang, Minji Kim, Su-Jung Kim, Yoon-Ji Kim, Sang-Jin Sung, Young Ho Kim, Sung-Hoon Lim, Namkug Kim, Seung-Hak Baek
Korean J Orthod.2022;52(4):287-297. Published online 2022 July 25
DOI: http://dx.doi.org/10.4041/kjod21.248
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| 6 |
Accuracy of one-step automated orthodontic diagnosis model using a convolutional neural network and lateral cephalogram images with different qualities obtained from nationwide multi-hospitals
Sunjin Yim, Sungchul Kim, Inhwan Kim, Jae-Woo Park, Jin-Hyoung Cho, Mihee Hong, Kyung-Hwa Kang, Minji Kim, Su-Jung Kim, Yoon-Ji Kim, Young Ho Kim, Sung-Hoon Lim, Sang Jin Sung, Namkug Kim, Seung-Hak Baek
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| 7 |
Evaluation of VGG-16 deep learning algorithm for dental caries classification
Min-Ji Byon, Eun-Joo Jun, Ji-Soo Kim, Jae-Joon Hwang, Seung-Hwa Jeong
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| 8 |
Evaluation of a multi-stage convolutional neural network-based fully automated landmark identification system using cone-beam computed tomography-synthesized posteroanterior cephalometric images
Min-Jung Kim, Yi Liu, Song Hee Oh, Hyo-Won Ahn, Seong-Hun Kim, Gerald Nelson
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| 9 |
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
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| 10 |
The Future of Capsule Endoscopy: The Role of Artificial Intelligence and Other Technical Advancements
Young Joo Yang
Clin Endosc.2020;53(4):387-394. Published online 2020 July 16
DOI: http://dx.doi.org/10.5946/ce.2020.133
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| 11 |
Lesion-Based Convolutional Neural Network in Diagnosis of Early Gastric Cancer
Hong Jin Yoon, Jie-Hyun Kim
Clin Endosc.2020;53(2):127-131. Published online 2020 March 30
DOI: http://dx.doi.org/10.5946/ce.2020.046
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| 12 |
Convolutional Neural Network Technology in Endoscopic Imaging: Artificial Intelligence for Endoscopy
Joonmyeong Choi, Keewon Shin, Jinhoon Jung, Hyun-Jin Bae, Do Hoon Kim, Jeong-Sik Byeon, Namku Kim
Clin Endosc.2020;53(2):117-126. Published online 2020 March 30
DOI: http://dx.doi.org/10.5946/ce.2020.054
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| 13 |
Feasibility of fully automated classification of whole slide images based on deep learning
Kyung-Ok Cho, Sung Hak Lee, Hyun-Jong Jang
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| 14 |
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
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| 15 |
The development of food image detection and recognition model of Korean food for mobile dietary management
Seon-Joo Park, Akmaljon Palvanov, Chang-Ho Lee, Nanoom Jeong, Young-Im Cho, Hae-Jeung Lee
Nutr Res Pract.2019;13(6):521-528. Published online 2019 November 21
DOI: http://dx.doi.org/10.4162/nrp.2019.13.6.521
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| 16 |
Fully Automatic Segmentation of Acute Ischemic Lesions on Diffusion-Weighted Imaging Using Convolutional Neural Networks: Comparison with Conventional Algorithms
Ilsang Woo, Areum Lee, Seung Chai Jung, Hyunna Lee, Namkug Kim, Se Jin Cho, Donghyun Kim, Jungbin Lee, Leonard Sunwoo, Dong-Wha Kang
Korean J Radiol.2019;20(8):1275-1284. Published online 2019 July 18
DOI: http://dx.doi.org/10.3348/kjr.2018.0615
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| 17 |
Medical Image Analysis Using Artificial Intelligence
Hyun Jin Yoon, Young Jin Jeong, Hyun Kang, Ji Eun Jeong, Do-Young Kang
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| 18 |
Development of Artificial Intelligence to Support Needle Electromyography Diagnostic Analysis
Sangwoo Nam, Min Kyun Sohn, Hyun Ah Kim, Hyoun-Joong Kong, Il-Young Jung
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| 19 |
Automatic Prediction of Atrial Fibrillation Based on Convolutional Neural Network Using a Short-term Normal Electrocardiogram Signal
Urtnasan Erdenebayar, Hyeonggon Kim, Jong-Uk Park, Dongwon Kang, Kyoung-Joung Lee
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| 20 |
Deep Learning for Cancer Screening in Medical Imaging
Jihoon Jeong
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