Gigon Bae

ORCID: 0000-0003-0648-9735
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About
Contact & Profiles
Research Areas
  • Software Engineering Research
  • Software Testing and Debugging Techniques
  • Software System Performance and Reliability
  • Artificial Intelligence in Healthcare and Education
  • Radiomics and Machine Learning in Medical Imaging
  • Software Reliability and Analysis Research
  • Manufacturing Process and Optimization
  • Genomic variations and chromosomal abnormalities
  • Medical Imaging and Analysis
  • Radiology practices and education
  • Cancer Genomics and Diagnostics
  • Advanced X-ray and CT Imaging
  • Collaboration in agile enterprises
  • Genomics and Phylogenetic Studies
  • Medical Image Segmentation Techniques
  • Advanced Numerical Analysis Techniques
  • Educational Technology and Assessment
  • Software Engineering Techniques and Practices

Nvidia (United States)
2017-2024

University of Nebraska–Lincoln
2015

Korea Advanced Institute of Science and Technology
2010-2014

Abstract Refactoring is a widely accepted technique to improve the software quality by restructuring its design without changing behavior. In general, sequence of refactorings needs be applied until code improved satisfactorily. this case, final after refactoring can vary with application order refactorings, thereby producing different improvements. Therefore, it necessary determine proper schedule obtain as many benefits possible. However, there little research on problem generating...

10.1002/spe.1031 article EN Software Practice and Experience 2010-12-29

Recording the sequence of events that lead to a failure web application can be an effective aid for debugging. Nevertheless, recording event may include many are not related failure, and this render debugging more difficult. To address problem, we have adapted Delta Debugging function on recordings applications, in manner lets it identify discard portions those do influence occurrence failure. We present results three empirical studies show (1) reduction achieve significant reductions size...

10.1145/2786805.2786846 article EN 2015-08-26

Artificial intelligence (AI) has become commonplace in solving routine everyday tasks. Because of the exponential growth medical imaging data volume and complexity, workload on radiologists is steadily increasing. AI been shown to improve efficiency image generation, processing, interpretation, various such models have developed across research laboratories worldwide. However, very few these, if any, find their way into clinical use, a discrepancy that reflects divide between successful...

10.2196/55833 article EN cc-by JMIR AI 2024-10-02

Many software systems rely on graphical-user interfaces (GUIs) to support user interactions. The correctness of these GUIs affects the overall quality systems, and thus, it is important that be tested. To such testing, GUI test case generation techniques based graph models as event flow graphs (EFGs) have been used generate cases in form sequences events. Models, however, are abstractions dynamic behavior may not accurately reflect actual system behavior, create nonexecutable miss Test...

10.1109/issre.2012.18 article EN 2012-11-01

Artificial Intelligence (AI) has become commonplace to solve routine everyday tasks. Because of the exponential growth in medical imaging data volume and complexity, workload on radiologists is steadily increasing. We project that gap between number exams expert radiologist readers required cover this increase will continue expand, consequently introducing a demand for AI-based tools improve efficiency with which can comfortably interpret these exams. AI been shown medical-image generation,...

10.48550/arxiv.2212.14177 preprint EN other-oa arXiv (Cornell University) 2022-01-01

<sec> <title>UNSTRUCTURED</title> Artificial intelligence (AI) has become commonplace in solving routine everyday tasks. Because of the exponential growth medical imaging data volume and complexity, workload on radiologists is steadily increasing. AI been shown to improve efficiency medical-image generation, processing, interpretation, various such models have developed across research labs worldwide. However, very few these, if any, find their way into clinical use, a discrepancy that...

10.2196/preprints.55833 preprint EN 2023-12-27

<ns3:p>In October 2019, 46 scientists from around the world participated in first National Center for Biotechnology Information (NCBI) Structural Variation (SV) Codeathon at Baylor College of Medicine. The charge this annual working session was to identify ongoing challenges topics SV and graph genomes, response design reliable methods facilitate their study. Over three days, seven groups each designed developed new open-sourced improve bioinformatic analysis genomic SVs represented...

10.12688/f1000research.23773.1 preprint EN cc-by F1000Research 2020-09-16
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