Joseph Bae

2.6k total citations
13 papers, 190 citations indexed

About

Joseph Bae is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Genetics. According to data from OpenAlex, Joseph Bae has authored 13 papers receiving a total of 190 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Artificial Intelligence and 3 papers in Genetics. Recurrent topics in Joseph Bae's work include Radiomics and Machine Learning in Medical Imaging (8 papers), COVID-19 diagnosis using AI (5 papers) and Glioma Diagnosis and Treatment (3 papers). Joseph Bae is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (8 papers), COVID-19 diagnosis using AI (5 papers) and Glioma Diagnosis and Treatment (3 papers). Joseph Bae collaborates with scholars based in United States, India and Germany. Joseph Bae's co-authors include Prateek Prasanna, Dimitris Samaras, Junjun He, Huidong Liu, Lei Zhou, Abhinav Vepa, Kamlesh Khunti, Faheem Ahmed, Manish Pareek and Chao Chen and has published in prestigious journals such as International Journal of Radiation Oncology*Biology*Physics, Journal of Clinical Medicine and Diabetes & Metabolic Syndrome Clinical Research & Reviews.

In The Last Decade

Joseph Bae

12 papers receiving 182 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Joseph Bae United States 7 70 43 39 38 29 13 190
Ying-Chun Jheng Taiwan 11 192 2.7× 41 1.0× 37 0.9× 29 0.8× 22 0.8× 23 345
Zeno Falaschi Italy 9 158 2.3× 42 1.0× 11 0.3× 53 1.4× 67 2.3× 18 260
Moezedin Javad Rafiee Canada 6 163 2.3× 93 2.2× 20 0.5× 45 1.2× 15 0.5× 18 225
Hitoshi Mori Japan 9 98 1.4× 135 3.1× 24 0.6× 31 0.8× 35 1.2× 65 449
John Gibson United States 7 89 1.3× 132 3.1× 17 0.4× 11 0.3× 37 1.3× 12 351
Guang Zhang China 11 66 0.9× 31 0.7× 48 1.2× 10 0.3× 45 1.6× 43 265
Victor Savevski Italy 13 202 2.9× 68 1.6× 20 0.5× 75 2.0× 87 3.0× 32 383
Mwaffaq El-Heis Jordan 8 52 0.7× 38 0.9× 27 0.7× 62 1.6× 9 0.3× 24 239
Renu P. Rajan India 8 288 4.1× 21 0.5× 27 0.7× 52 1.4× 19 0.7× 31 397
Benjamin Irving United Kingdom 9 130 1.9× 22 0.5× 43 1.1× 48 1.3× 11 0.4× 19 202

Countries citing papers authored by Joseph Bae

Since Specialization
Citations

This map shows the geographic impact of Joseph Bae'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 Joseph Bae with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joseph Bae more than expected).

Fields of papers citing papers by Joseph Bae

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joseph Bae. 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 Joseph Bae. The network helps show where Joseph Bae may publish in the future.

Co-authorship network of co-authors of Joseph Bae

This figure shows the co-authorship network connecting the top 25 collaborators of Joseph Bae. A scholar is included among the top collaborators of Joseph Bae 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 Joseph Bae. Joseph Bae is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
Bae, Joseph, et al.. (2025). Spatial Radiomic Graphs for Outcome Prediction in Radiation Therapy–treated Head and Neck Squamous Cell Carcinoma Using Pretreatment CT. Radiology Imaging Cancer. 7(2). e240161–e240161. 1 indexed citations
2.
3.
Singh, Gagandeep, Joseph Bae, Sunil Manjila, et al.. (2024). New frontiers in domain-inspired radiomics and radiogenomics: increasing role of molecular diagnostics in CNS tumor classification and grading following WHO CNS-5 updates. Cancer Imaging. 24(1). 133–133. 2 indexed citations
4.
Zhou, Lei, Huidong Liu, Joseph Bae, et al.. (2023). Self Pre-Training with Masked Autoencoders for Medical Image Classification and Segmentation. 1–6. 57 indexed citations
5.
Hu, Xiaoling, et al.. (2023). Enhancing Modality-Agnostic Representations via Meta-learning for Brain Tumor Segmentation. PubMed. 2023. 21358–21368. 13 indexed citations
6.
7.
Xu, Xuan, et al.. (2022). Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 18802–18813. 13 indexed citations
8.
Bae, Joseph, Gagandeep Singh, Jeremy Green, et al.. (2021). Predicting COVID-19 Lung Infiltrate Progression on Chest Radiographs Using Spatio-temporal LSTM based Encoder-Decoder Network. 384–398. 2 indexed citations
9.
Patwa, Parth, et al.. (2021). COVID-19 Outbreak Prediction and Analysis using Self Reported Symptoms. 154–169. 1 indexed citations
10.
11.
Vepa, Abhinav, Joseph Bae, Faheem Ahmed, Manish Pareek, & Kamlesh Khunti. (2020). COVID-19 and ethnicity: A novel pathophysiological role for inflammation. Diabetes & Metabolic Syndrome Clinical Research & Reviews. 14(5). 1043–1051. 45 indexed citations
12.
13.
Seung, Steven K., Joseph Bae, Matthew C. Solhjem, et al.. (2008). Intensity-Modulated Radiotherapy for Head-and-Neck Cancer in the Community Setting. International Journal of Radiation Oncology*Biology*Physics. 72(4). 1075–1081. 20 indexed citations

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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2026