Justin Jee

1.2k total citations
28 papers, 340 citations indexed

About

Justin Jee is a scholar working on Oncology, Cancer Research and Infectious Diseases. According to data from OpenAlex, Justin Jee has authored 28 papers receiving a total of 340 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Oncology, 7 papers in Cancer Research and 6 papers in Infectious Diseases. Recurrent topics in Justin Jee's work include COVID-19 and healthcare impacts (11 papers), Cancer Genomics and Diagnostics (7 papers) and COVID-19 Clinical Research Studies (6 papers). Justin Jee is often cited by papers focused on COVID-19 and healthcare impacts (11 papers), Cancer Genomics and Diagnostics (7 papers) and COVID-19 Clinical Research Studies (6 papers). Justin Jee collaborates with scholars based in United States, Canada and Japan. Justin Jee's co-authors include Aaron J. Stonestrom, Varun Narendra, Melissa S. Pessin, Michael B. Foote, Luis A. Díaz, Yelena Y. Janjigian, Viswatej Avutu, Melissa Lumish, Rimma Belenkaya and Beatriz Wills and has published in prestigious journals such as Nature Communications, Nature Genetics and Journal of Clinical Oncology.

In The Last Decade

Justin Jee

22 papers receiving 337 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Justin Jee United States 9 252 143 49 44 42 28 340
Wenjuan He China 7 267 1.1× 306 2.1× 52 1.1× 28 0.6× 34 0.8× 14 513
Rimma Belenkaya United States 5 165 0.7× 88 0.6× 47 1.0× 25 0.6× 33 0.8× 7 278
Hagar Elghazawy Egypt 9 182 0.7× 62 0.4× 60 1.2× 34 0.8× 14 0.3× 19 284
Elissar Moujaess Lebanon 6 226 0.9× 89 0.6× 39 0.8× 35 0.8× 15 0.4× 9 318
Chiara Citterio Italy 12 221 0.9× 143 1.0× 98 2.0× 24 0.5× 20 0.5× 47 381
Nahila Justo Sweden 10 150 0.6× 79 0.6× 88 1.8× 31 0.7× 16 0.4× 21 418
Abdullah A. Alsharm Saudi Arabia 6 209 0.8× 31 0.2× 46 0.9× 24 0.5× 41 1.0× 18 307
Sheenu Chandwani United States 13 251 1.0× 84 0.6× 124 2.5× 44 1.0× 30 0.7× 33 522
Javier Louro Spain 12 241 1.0× 59 0.4× 86 1.8× 57 1.3× 12 0.3× 30 400
Kristen Labbe United States 6 146 0.6× 65 0.5× 51 1.0× 14 0.3× 31 0.7× 6 233

Countries citing papers authored by Justin Jee

Since Specialization
Citations

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

Fields of papers citing papers by Justin Jee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Justin Jee

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

All Works

20 of 20 papers shown
1.
Tran, Thinh Ngoc, Chris Fong, Karl Pichotta, et al.. (2025). AI cancer driver mutation predictions are valid in real-world data. Nature Communications. 16(1). 8509–8509.
2.
Jiang, Jue, Justin Jee, Michele Waters, et al.. (2025). Large language model trained on clinical oncology data predicts cancer progression. npj Digital Medicine. 8(1). 397–397. 3 indexed citations
3.
4.
Bakouny, Ziad, Chris Fong, Michele Waters, et al.. (2025). Use of a large language model (LLM) for pan-cancer automated detection of anti-cancer therapy toxicities and translational toxicity research.. Journal of Clinical Oncology. 43(16_suppl). 1558–1558.
5.
Liu, Dazhi, et al.. (2024). Characterization of diverse targetable ERBB2 alterations in 512,993 patients with solid tumors.. Journal of Clinical Oncology. 42(16_suppl). 3129–3129. 1 indexed citations
6.
Tang, Cerise, Michele Waters, Chris Fong, et al.. (2024). Obesity-dependent selection of driver mutations in cancer. Nature Genetics. 56(11). 2318–2321. 6 indexed citations
7.
Kehl, Kenneth L., Justin Jee, Christopher J. Fong, et al.. (2024). Shareable artificial intelligence to extract cancer outcomes from electronic health records for precision oncology research. Nature Communications. 15(1). 9787–9787. 9 indexed citations
8.
Tran, Thinh Ngoc, Chris Fong, Anisha Luthra, et al.. (2024). Abstract 1252: AI-derived predictions improve identification of real-world cancer driver mutations. Cancer Research. 84(6_Supplement). 1252–1252.
9.
Gormally, Michael V., Matteo Repetto, Justin Jee, et al.. (2024). A pan-cancer analysis of SMARCA4 alterations and the unique clinicogenomic characteristics associated with SMARCA4 mutation types.. Journal of Clinical Oncology. 42(16_suppl). 3073–3073. 1 indexed citations
10.
Stonestrom, Aaron J., Kamal Menghrajani, Sean M. Devlin, et al.. (2023). High-risk and silent clonal hematopoietic genotypes in patients with nonhematologic cancer. Blood Advances. 8(4). 846–856. 5 indexed citations
11.
Jee, Justin, Robert B. Keller, Alexa B. Schrock, et al.. (2023). MA06.08 Real-World Landscape Analysis of Activating ERBB2/ERBB3 Alterations in 107,561 Tissue and Plasma Samples from Patients with NSCLC. Journal of Thoracic Oncology. 18(11). S120–S121.
12.
Zhang, Allen W., Sejal Morjaria, Anna Kaltsas, et al.. (2021). The Effect of Neutropenia and Filgrastim (G-CSF) on Cancer Patients With Coronavirus Disease 2019 (COVID-19) Infection. Clinical Infectious Diseases. 74(4). 567–574. 24 indexed citations
13.
Jee, Justin, Aaron J. Stonestrom, Sean M. Devlin, et al.. (2021). Oncologic immunomodulatory agents in patients with cancer and COVID-19. Scientific Reports. 11(1). 4814–4814. 10 indexed citations
14.
Lara, Olivia D., Yuyan Wang, Roisin E. O’Cearbhaill, et al.. (2021). COVID-19 outcomes of patients with gynecologic cancer in New York City: an updated analysis. Gynecologic Oncology. 162. S22–S23. 1 indexed citations
15.
Stahl, Maximilian, Varun Narendra, Justin Jee, et al.. (2021). Neutropenia in adult acute myeloid leukemia patients represents a powerful risk factor for COVID-19 related mortality. Leukemia & lymphoma. 62(8). 1940–1948. 7 indexed citations
16.
Jee, Justin, Michael B. Foote, Melissa Lumish, et al.. (2020). Chemotherapy and COVID-19 Outcomes in Patients With Cancer. Journal of Clinical Oncology. 38(30). 3538–3546. 173 indexed citations
17.
Lara, Olivia D., Roisin E. O’Cearbhaill, Anne Knisely, et al.. (2020). Inflammatory markers in gynecologic oncology patients hospitalized with COVID-19 infection. Gynecologic Oncology. 159(3). 618–622. 9 indexed citations
18.
Bolton, Kelly L., Michael B. Foote, Justin Jee, et al.. (2020). Clonal Hematopoiesis and COVID-19 Severity in Cancer Patients. Blood. 136(Supplement 1). 37–38. 1 indexed citations
19.
Lara, Olivia D., Yuyan Wang, Roisin E. O’Cearbhaill, et al.. (2020). Racial disparities in patients with coronavirus disease 2019 infection and gynecologic malignancy. Cancer. 127(7). 1057–1067. 7 indexed citations
20.
Lim, In Kyoung, et al.. (1999). Differential expression of O   6 -methylguanine-DNA methyltransferase during diethylnitrosamine-induced carcinogenesis and liver regeneration in Sprague-Dawley male rats. Journal of Cancer Research and Clinical Oncology. 125(8-9). 493–499. 12 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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