Hwejin Jung

738 total citations
4 papers, 215 citations indexed

About

Hwejin Jung is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Hwejin Jung has authored 4 papers receiving a total of 215 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Radiology, Nuclear Medicine and Imaging, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Artificial Intelligence. Recurrent topics in Hwejin Jung's work include Radiomics and Machine Learning in Medical Imaging (2 papers), COVID-19 diagnosis using AI (2 papers) and AI in cancer detection (2 papers). Hwejin Jung is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (2 papers), COVID-19 diagnosis using AI (2 papers) and AI in cancer detection (2 papers). Hwejin Jung collaborates with scholars based in South Korea and Japan. Hwejin Jung's co-authors include Jaewoo Kang, Junhyun Lee, Bumsoo Kim, Soo‐Youn Ham and Bumsoo Kim and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and BMC Medical Imaging.

In The Last Decade

Hwejin Jung

4 papers receiving 209 citations

Peers

Countries citing papers authored by Hwejin Jung

Since Specialization

Citations

This map shows the geographic impact of Hwejin Jung's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hwejin Jung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hwejin Jung more than expected).

Fields of papers citing papers by Hwejin Jung

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hwejin Jung. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hwejin Jung. The network helps show where Hwejin Jung may publish in the future.

Co-authorship network of co-authors of Hwejin Jung

This figure shows the co-authorship network connecting the top 25 collaborators of Hwejin Jung. A scholar is included among the top collaborators of Hwejin Jung based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hwejin Jung. Hwejin Jung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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4 of 4 papers shown

#	Work	Indexed citations
1	An automatic nuclei segmentation method based on deep convolutional neural networks for histopathology images 2019 ·SHILAP Revista de lepidopterología ·Hwejin Jung, (unknown), Jaewoo Kang	56
2	Detection of masses in mammograms using a one-stage object detector based on a deep convolutional neural network 2018 ·PLoS ONE ·Hwejin Jung, Bumsoo Kim, (unknown), (unknown), Junhyun Lee, Soo‐Youn Ham, (unknown), Jaewoo Kang	94
3	Classification of lung nodules in CT scans using three-dimensional deep convolutional neural networks with a checkpoint ensemble method 2018 ·BMC Medical Imaging ·Hwejin Jung, (unknown), (unknown), Junhyun Lee, Jaewoo Kang	64
4	Pulmonary Nodule Classification in Computed Tomography Image Using a 3D Deep Convolutional Neural Network 2018 ·KIISE Transactions on Computing Practices ·Hwejin Jung, Bumsoo Kim, (unknown), Junhyun Lee, Jaewoo Kang	1

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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