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Journal of the Korean Society of Radiology
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October 17, 2024
[Explainable & Safe Artificial Intelligence in Radiology]
Synho Do
Radiology. Artificial Intelligence
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May 8, 2024
Artificial Intelligence for Breast Cancer Screening: Trade-offs between Sensitivity and Specificity
Manisha Bahl, Synho Do
AJR. American Journal of Roentgenology
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May 24, 2023
Beyond the <i>AJR</i>: An International Competition Advances Artificial Intelligence Research
Manisha Bahl, Synho Do
Radiology
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June 20, 2023
Artificial Intelligence Applied to Contrast-enhanced Mammography: Exploring Uncharted Territory
Manisha Bahl, Synho Do
Radiology. Artificial Intelligence
|
December 17, 2025
Mapping the AI "Mind": What the AI-STREAM Trial Reveals About Cancers Detected and Missed
Synho Do, Manisha Bahl
Abdominal Imaging : Computation and Clinical Applications : 5Th International Workshop, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013 : Proceedings. Abdominal Imaging (Workshop) (5Th : 2013 : Nagoya-Shi, Japan)
|
January 13, 2015
Computer-Aided Detection of Colorectal Lesions with Super-Resolution CT Colonography: Pilot Evaluation
Janne J Näppi, Synho Do, Hiroyuki Yoshida
Korean Journal of Radiology
|
January 11, 2020
Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning
Synho Do, Kyoung Doo Song, Joo Won Chung
AJR. American Journal of Roentgenology
|
December 3, 2025
Commercial Artificial Intelligence (AI) Tool for Screening Digital Breast Tomosynthesis: Factors Associated With AI-Based Breast Cancer Detection
Manisha Bahl, Kyungsu Kim, Hyunji Kim, et al.
Computers in Biology and Medicine
|
March 3, 2022
A scalable artificial intelligence platform that automatically finds copy number variations (CNVs) in journal articles and transforms them into a database: CNV extraction, transformation, and loading AI (CNV-ETLAI)
Jongmun Choi, Soomin Jeon, Doyun Kim, et al.
Journal of Digital Imaging
|
October 7, 2017
A Deep-Learning System for Fully-Automated Peripherally Inserted Central Catheter (PICC) Tip Detection
Hyunkwang Lee, Mohammad Mansouri, Shahein Tajmir, et al.
Page
of 8
Search research articles
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Showing results (1-10 of 74) with videos related to
Sort By:
Page
of 8
Journal of the Korean Society of Radiology
|
October 17, 2024
[Explainable & Safe Artificial Intelligence in Radiology]
Synho Do
Radiology. Artificial Intelligence
|
May 8, 2024
Artificial Intelligence for Breast Cancer Screening: Trade-offs between Sensitivity and Specificity
Manisha Bahl, Synho Do
AJR. American Journal of Roentgenology
|
May 24, 2023
Beyond the <i>AJR</i>: An International Competition Advances Artificial Intelligence Research
Manisha Bahl, Synho Do
Radiology
|
June 20, 2023
Artificial Intelligence Applied to Contrast-enhanced Mammography: Exploring Uncharted Territory
Manisha Bahl, Synho Do
Radiology. Artificial Intelligence
|
December 17, 2025
Mapping the AI "Mind": What the AI-STREAM Trial Reveals About Cancers Detected and Missed
Synho Do, Manisha Bahl
Abdominal Imaging : Computation and Clinical Applications : 5Th International Workshop, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013 : Proceedings. Abdominal Imaging (Workshop) (5Th : 2013 : Nagoya-Shi, Japan)
|
January 13, 2015
Computer-Aided Detection of Colorectal Lesions with Super-Resolution CT Colonography: Pilot Evaluation
Janne J Näppi, Synho Do, Hiroyuki Yoshida
Korean Journal of Radiology
|
January 11, 2020
Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning
Synho Do, Kyoung Doo Song, Joo Won Chung
AJR. American Journal of Roentgenology
|
December 3, 2025
Commercial Artificial Intelligence (AI) Tool for Screening Digital Breast Tomosynthesis: Factors Associated With AI-Based Breast Cancer Detection
Manisha Bahl, Kyungsu Kim, Hyunji Kim, et al.
Computers in Biology and Medicine
|
March 3, 2022
A scalable artificial intelligence platform that automatically finds copy number variations (CNVs) in journal articles and transforms them into a database: CNV extraction, transformation, and loading AI (CNV-ETLAI)
Jongmun Choi, Soomin Jeon, Doyun Kim, et al.
Journal of Digital Imaging
|
October 7, 2017
A Deep-Learning System for Fully-Automated Peripherally Inserted Central Catheter (PICC) Tip Detection
Hyunkwang Lee, Mohammad Mansouri, Shahein Tajmir, et al.
Page
of 8