Joy T. Wu

812 total citations
22 papers, 451 citations indexed

About

Joy T. Wu is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Joy T. Wu has authored 22 papers receiving a total of 451 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 13 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Molecular Biology. Recurrent topics in Joy T. Wu's work include COVID-19 diagnosis using AI (10 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Machine Learning in Healthcare (6 papers). Joy T. Wu is often cited by papers focused on COVID-19 diagnosis using AI (10 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Machine Learning in Healthcare (6 papers). Joy T. Wu collaborates with scholars based in United States, Taiwan and Germany. Joy T. Wu's co-authors include Leo Anthony Celi, Tanveer Syeda-Mahmood, Yeran Li, Eric T. Carlson, Franck Dernoncourt, Edward T. Moseley, Jonathan Welt, Patrick D. Tyler, Sebastian Gehrmann and Alexandros Karargyris and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Electron Devices and Radiographics.

In The Last Decade

Joy T. Wu

21 papers receiving 427 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Joy T. Wu United States	10	205	173	90	86	52	22	451
Lin Guo China	13	98 0.5×	159 0.9×	48 0.5×	116 1.3×	32 0.6×	57	542
Jiebin Chen China	10	84 0.4×	69 0.4×	108 1.2×	52 0.6×	41 0.8×	19	417
Kevin Faust Canada	8	172 0.8×	164 0.9×	149 1.7×	37 0.4×	25 0.5×	12	380
Bradley J. Nartowt United States	7	190 0.9×	236 1.4×	64 0.7×	37 0.4×	47 0.9×	13	427
Sharifa Sahai United States	2	299 1.5×	213 1.2×	141 1.6×	62 0.7×	36 0.7×	3	585
Pritam Mukherjee United States	12	149 0.7×	316 1.8×	80 0.9×	44 0.5×	17 0.3×	39	484
Colin B. Compas United States	7	262 1.3×	190 1.1×	182 2.0×	75 0.9×	68 1.3×	15	618
Joshua Levy United States	13	196 1.0×	102 0.6×	72 0.8×	155 1.8×	15 0.3×	72	639
Malgorzata Polacin Switzerland	10	140 0.7×	273 1.6×	119 1.3×	60 0.7×	22 0.4×	28	646
Ramsey M. Wehbe United States	10	116 0.6×	139 0.8×	85 0.9×	82 1.0×	20 0.4×	24	389

Countries citing papers authored by Joy T. Wu

Since Specialization

Citations

This map shows the geographic impact of Joy T. Wu'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 Joy T. Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joy T. Wu more than expected).

Fields of papers citing papers by Joy T. Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joy T. Wu. 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 Joy T. Wu. The network helps show where Joy T. Wu may publish in the future.

Co-authorship network of co-authors of Joy T. Wu

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

All Works

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20 of 20 papers shown

Guja, Kip E., et al.. (2025). Adverse Events in Targeted Radionuclide Therapy. Radiographics. 45(9). e240143–e240143.

Lourentzou, Ismini, et al.. (2023). Fairness metrics for health AI: we have a long way to go. EBioMedicine. 90. 104525–104525. 10 indexed citations

Wang, Hongzhi, Joy T. Wu, Lucia Baratto, et al.. (2023). Multimodal Pediatric Lymphoma Detection using PET and MRI.. PubMed. 2023. 736–743. 4 indexed citations

Wu, Joy T., Miguel Ángel Armengol de la Hoz, Po‐Chih Kuo, et al.. (2022). Developing and Validating Multi-Modal Models for Mortality Prediction in COVID-19 Patients: a Multi-center Retrospective Study. Journal of Digital Imaging. 35(6). 1514–1529. 9 indexed citations

Han, Mina, et al.. (2021). Curation of the CANDID-PTX Dataset with Free-Text Reports. Radiology Artificial Intelligence. 3(6). e210136–e210136. 13 indexed citations

Jadhav, Ashutosh, et al.. (2021). Semantic Expansion of Clinician Generated Data Preferences for Automatic Patient Data Summarization.. PubMed. 2021. 571–580. 1 indexed citations

Shivade, Chaitanya, Satyananda Kashyap, Joy T. Wu, et al.. (2020). Towards Visual Dialog for Radiology. 60–69. 21 indexed citations

Wu, Joy T., Yaniv Gur, Alexandros Karargyris, et al.. (2020). Automatic Bounding Box Annotation of Chest X-Ray Data for Localization of Abnormalities. 799–803. 12 indexed citations

Wu, Joy T., Ali Syed, Yaniv Gur, et al.. (2020). AI Accelerated Human-in-the-loop Structuring of Radiology Reports.. PubMed. 2020. 1305–1314. 8 indexed citations

10.

Jadhav, Ashutosh, Ken C. L. Wong, Joy T. Wu, Mehdi Moradi, & Tanveer Syeda-Mahmood. (2020). Combining Deep Learning and Knowledge-driven Reasoning for Chest X-Ray Findings Detection.. PubMed. 2020. 593–601. 4 indexed citations

11.

Kashyap, Satyananda, Alexandros Karargyris, Joy T. Wu, et al.. (2020). Looking in the Right Place for Anomalies: Explainable Ai Through Automatic Location Learning. arXiv (Cornell University). 1125–1129. 9 indexed citations

12.

Wu, Joy T., Ken C. L. Wong, Yaniv Gur, et al.. (2020). Comparison of Chest Radiograph Interpretations by Artificial Intelligence Algorithm vs Radiology Residents. JAMA Network Open. 3(10). e2022779–e2022779. 91 indexed citations

13.

Syeda-Mahmood, Tanveer, Nadeem A. Ansari, Yaniv Gur, et al.. (2019). Building a Benchmark Dataset and Classifiers for Sentence-Level Findings in AP Chest X-Rays. 863–867. 1 indexed citations

14.

Moradi, Mehdi, Eliot L. Siegel, Satyananda Kashyap, et al.. (2019). Artificial intelligence for point of care radiograph quality assessment. 128–128. 9 indexed citations

15.

Karargyris, Alexandros, Satyananda Kashyap, Joy T. Wu, et al.. (2019). Age prediction using a large chest x-ray dataset. 66–66. 23 indexed citations

16.

Gehrmann, Sebastian, Franck Dernoncourt, Yeran Li, et al.. (2018). Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives. PLoS ONE. 13(2). e0192360–e0192360. 146 indexed citations

17.

Wu, Joy T., Franck Dernoncourt, Sebastian Gehrmann, et al.. (2017). Behind the scenes: A medical natural language processing project. International Journal of Medical Informatics. 112. 68–73. 26 indexed citations

18.

Raffa, Jesse D., et al.. (2017). Predicting medical nonadherence using natural language processing. 7. 1–4. 2 indexed citations

19.

Wu, Joy T. & Jesús A. del Alamo. (2010). Fabrication and Characterization of Through-Substrate Interconnects. IEEE Transactions on Electron Devices. 57(6). 1261–1268. 15 indexed citations

20.

King, Tsoo E., Tomo̧ko Ohnishi, Daryl B. Winter, & Joy T. Wu. (1976). Biochemical and EPR Probes for Structure-Function Studies of Iron Sulfur Centers of Succinate Dehydrogenase. Advances in experimental medicine and biology. 74. 182–227. 44 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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