Skip Navigation
Skip to contents
Results by Year

View Wide

Filter

ARTICLE TYPE

more+
SELECT FILTER
 
Close

PUBLICATION DATE

145 results
Display

Crew Resource Management in Industry 4.0: Focusing on Human-Autonomy Teaming

Yun S, Woo S

In the era of the 4th industrial revolution, the aviation industry is also growing remarkably with the development of artificial intelligence and networks, so it is necessary to study a...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Editorial for Vol. 31, No. 2

Kim YH

In Vol. 31, No. 2, our journal prepared a review article, two original papers, and three case reports. First, autonomous systems are increasingly being introduced in aircraft systems. Therefore, it...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Recurrent Neural Network Based Drug Repurposing to Address SARS-CoV-2 (COVID-19), and the in vitro Antiviral Efficacy of Peroxisome Proliferator-Activated Receptors-Gamma Agonist

Kim NH, Dong JJ

Background: Acute respiratory distress syndrome resulting from coronavirus (COVID-19) infection is triggered by cytokine storms, so activation of inhibitory modulators of inflammatory pathways has become a new candidate modality for...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
The Application of Machine Learning in Predicting Outcome of Cryotherapy and Immunotherapy for Wart Removal

Singh Y

Background: Warts can be extremely painful conditions that may be associated with localised bleeding and discharge. They are commonly treated by cryotherapy or immunotherapy. However, each of these therapies have discomforting...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Deep Learning-Based Artificial Intelligence for Mammography

Yoon JH, Kim EK

During the past decade, researchers have investigated the use of computer-aided mammography interpretation. With the application of deep learning technology, artificial intelligence (AI)-based algorithms for mammography have shown promising results...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Validation of an Automatic Tagging System for Identifying Respiratory and Hemodynamic Deterioration Events in the Intensive Care Unit

Jeddah D, Chen O, Lipsky AM, Forgacs A, Celniker G, Lilly CM, Pessach IM

Objectives: Predictive models for critical events in the intensive care unit (ICU) might help providers anticipate patient deterioration. At the heart of predictive model development lies the ability to accurately...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Machine Learning for Antibiotic Resistance Prediction: A Prototype Using Off-the-Shelf Techniques and Entry-Level Data to Guide Empiric Antimicrobial Therapy

Feretzakis G, Sakagianni A, Loupelis E, Kalles D, Skarmoutsou N, Martsoukou M, Christopoulos C, Lada M, Petropoulou S, Velentza A, Michelidou S, Chatzikyriakou R, Dimitrellos E

Objectives: In the era of increasing antimicrobial resistance, the need for early identification and prompt treatment of multi-drug-resistant infections is crucial for achieving favorable outcomes in critically ill patients. As...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Artificial Intelligence and Echocardiography

Yoon YE, Kim S, Chang HJ

Artificial intelligence (AI) is evolving in the field of diagnostic medical imaging, including echocardiography. Although the dynamic nature of echocardiography presents challenges beyond those of static images from X-ray, computed...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Cycle-Consistent Generative Adversarial Network: Effect on Radiation Dose Reduction and Image Quality Improvement in Ultralow-Dose CT for Evaluation of Pulmonary Tuberculosis

Yan C, Lin J, Li H, Xu J, Zhang T, Chen H, Woodruff HC, Wu G, Zhang S, Xu Y, Lambin P

Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Diagnostic Performance of Deep Learning-Based Lesion Detection Algorithm in CT for Detecting Hepatic Metastasis from Colorectal Cancer

Kim K, Kim S, Han K, Bae H, Shin J, Lim JS

Objective: To compare the performance of the deep learning-based lesion detection algorithm (DLLD) in detecting liver metastasis with that of radiologists. Materials and Methods: This clinical retrospective study used 4386-slice computed...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Prediction of Patient Management in COVID-19 Using Deep Learning-Based Fully Automated Extraction of Cardiothoracic CT Metrics and Laboratory Findings

Weikert T, Rapaka S, Grbic S, Re T, Chaganti S, Winkel DJ, Anastasopoulos C, Niemann T, Wiggli BJ, Bremerich J, Twerenbold R, Sommer G, Comaniciu D, Sauter AW

Objective: To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavirus disease 2019 (COVID-19) using a fully automated deep learning-based approach and assess their potential to predict...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Automated Bone Age Assessment Using Artificial Intelligence: The Future of Bone Age Assessment

Lee BD, Lee MS

Bone age assessments are a complicated and lengthy process, which are prone to inter- and intra-observer variabilities. Despite the great demand for fully automated systems, developing an accurate and robust...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Artificial Intelligence in Lower Gastrointestinal Endoscopy: The Current Status and Future Perspective

Milluzzo SM, Cesaro P, Grazioli LM, Olivari N, Spada C

The present manuscript aims to review the history, recent advances, evidence, and challenges of artificial intelligence (AI) in colonoscopy. Although it is mainly focused on polyp detection and characterization, it...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Application of Artificial Intelligence in the Detection and Characterization of Colorectal Neoplasm

Kim KO, Kim EY

Endoscpists always have tried to pursue a perfect colonoscopy, and application of artificial intelligence (AI) using deep-learning algorithms is one of the promising supportive options for detection and characterization of...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Video Archiving and Communication System (VACS): A Progressive Approach, Design, Implementation, and Benefits for Surgical Videos

Kim D, Hwang W, Bae J, Park H, Kim KG

Objectives: As endoscopic, laparoscopic, and robotic surgical procedures become more common, surgical videos are increasingly being treated as records and serving as important data sources for education, research, and developing...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Mediating Effects of Smartphone Utilization between Attitude and Willingness to Use Home-Based Healthcare ICT among Older Adults

Jo HS, Hwang YS, Dronina Y

Objectives: This study explored the direct and indirect effects of knowledge of new technology (e.g., artificial intelligence, the Internet of Things, and the Fourth Industrial Revolution), attitudes towards technology use,...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Factors Associated with Worsening Oxygenation in Patients with Non-severe COVID-19 Pneumonia

Hahm CR, Lee YK, Oh DH, Ahn MY, Choi JP, Kang NR, Oh J, Choi H, Kim S

Background: This study aimed to determine the parameters for worsening oxygenation in non-severe coronavirus disease 2019 (COVID-19) pneumonia. Methods: This retrospective cohort study included cases of confirmed COVID-19 pneumonia in a...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Diagnostic Performance of a New Convolutional Neural Network Algorithm for Detecting Developmental Dysplasia of the Hip on Anteroposterior Radiographs

Park HS, Jeon K, Cho YJ, Kim SW, Lee SB, Choi G, Lee S, Choi YH, Cheon JE, Kim WS, Ryu YJ, Hwang JY

Objective: To evaluate the diagnostic performance of a deep learning algorithm for the automated detection of developmental dysplasia of the hip (DDH) on anteroposterior (AP) radiographs. Materials and Methods: Of 2601...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Artificial intelligence in breast ultrasonography

Kim J, Kim HJ, Kim C, Kim WH

Although breast ultrasonography is the mainstay modality for differentiating between benign and malignant breast masses, it has intrinsic problems with false positives and substantial interobserver variability. Artificial intelligence (AI), particularly...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Application of artificial intelligence in toxicopathology

Kang JS

Traditionally, pathologists examine tissue slides under a microscope to find pathological lesions, and have the burden of finding the lesions among so many histopathology slides. Furthermore, inconsistency of diagnoses results...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close

Go to Top

Copyright © 2021 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr