Michael Donovan

8.3k total citations · 4 hit papers
137 papers, 4.9k citations indexed

About

Michael Donovan is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Michael Donovan has authored 137 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Molecular Biology, 43 papers in Pulmonary and Respiratory Medicine and 26 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Michael Donovan's work include Prostate Cancer Diagnosis and Treatment (25 papers), Prostate Cancer Treatment and Research (25 papers) and Radiomics and Machine Learning in Medical Imaging (21 papers). Michael Donovan is often cited by papers focused on Prostate Cancer Diagnosis and Treatment (25 papers), Prostate Cancer Treatment and Research (25 papers) and Radiomics and Machine Learning in Medical Imaging (21 papers). Michael Donovan collaborates with scholars based in United States, China and United Kingdom. Michael Donovan's co-authors include Weihong Tan, Jian‐Hui Jiang, Guizhi Zhu, Johan Skog, Mikkel Noerholm, Erqun Song, James M. McKiernan, Gordon Brown, Kejing Zhang and Chen Liu and has published in prestigious journals such as Chemical Reviews, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Michael Donovan

125 papers receiving 4.9k citations

Hit Papers

Aptamers from Cell-Based ... 2013 2026 2017 2021 2013 2016 2013 2018 100 200 300 400 500

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Michael Donovan 3.0k 945 942 900 465 137 4.9k
Ruimin Huang 2.3k 0.8× 814 0.9× 1.6k 1.7× 357 0.4× 655 1.4× 139 5.0k
Zhuo Chen 3.3k 1.1× 1.4k 1.5× 1.8k 1.9× 377 0.4× 724 1.6× 80 6.5k
Kwanghee Kim 1.9k 0.6× 487 0.5× 590 0.6× 933 1.0× 679 1.5× 104 5.3k
Bhuvaneswari Ramaswamy 1.9k 0.6× 1.3k 1.3× 1.2k 1.3× 1.3k 1.5× 397 0.9× 161 4.9k
Patrycja Nowak‐Sliwinska 1.9k 0.6× 835 0.9× 1.1k 1.2× 970 1.1× 649 1.4× 101 5.0k
Yun Wu 2.9k 1.0× 1.2k 1.3× 1.2k 1.2× 257 0.3× 304 0.7× 113 5.1k
Congjian Xu 2.1k 0.7× 873 0.9× 1.3k 1.3× 399 0.4× 1.3k 2.8× 158 4.9k
Claire Rodriguez‐Lafrasse 1.9k 0.6× 587 0.6× 479 0.5× 1.0k 1.2× 169 0.4× 124 4.3k
Wayne L. Monsky 1.7k 0.5× 788 0.8× 1.6k 1.7× 721 0.8× 350 0.8× 84 5.2k
Annette T. Byrne 1.6k 0.5× 827 0.9× 1.4k 1.5× 1.3k 1.4× 994 2.1× 71 4.8k

Countries citing papers authored by Michael Donovan

Since Specialization
Citations

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

Fields of papers citing papers by Michael Donovan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Donovan

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Donovan. A scholar is included among the top collaborators of Michael Donovan 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 Michael Donovan. Michael Donovan 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.
Couch, John A., et al.. (2025). Advances in Targeted Therapy for Non-Small-Cell Lung Cancer: Current Progress and Future Directions. International Journal of Molecular Sciences. 26(23). 11517–11517.
2.
Lam, David W., Stephanie Wang, Nidhi Naik, et al.. (2024). A Real-World Precision Medicine Program Including the KidneyIntelX Test Effectively Changes Management Decisions and Outcomes for Patients With Early-Stage Diabetic Kidney Disease. Journal of Primary Care & Community Health. 15. 4277843597–4277843597. 5 indexed citations
4.
Schneider, John E., et al.. (2023). Cost-effectiveness analysis of LungLB for the clinical management of patients with indeterminate pulmonary nodules. Journal of Medical Economics. 26(1). 342–347. 1 indexed citations
5.
Tutrone, Ronald, Michael Donovan, Yiyuan Yao, et al.. (2023). ExoDx prostate test as a predictor of outcomes of high-grade prostate cancer – an interim analysis. Prostate Cancer and Prostatic Diseases. 26(3). 596–601. 33 indexed citations
6.
Fernández, Gerardo, Jack Zeineh, Marcel Prastawa, et al.. (2023). Analytical Validation of the PreciseDx Digital Prognostic Breast Cancer Test in Early-Stage Breast Cancer. Clinical Breast Cancer. 24(2). 93–102.e6. 2 indexed citations
7.
Rutland, John W., Corey M. Gill, Ethan Ellis, et al.. (2023). NF2 mutation associated with accelerated time to recurrence for older patients with atypical meningiomas. British Journal of Neurosurgery. 39(2). 173–179. 1 indexed citations
8.
Rutland, John W., Corey M. Gill, Daniel Ranti, et al.. (2022). Association of mutations in DNA polymerase epsilon with increased CD8+ cell infiltration and prolonged progression-free survival in patients with meningiomas. Neurosurgical FOCUS. 52(2). E7–E7. 5 indexed citations
9.
Naik, Nidhi, Stephanie Wang, Azadeh Zabetian, et al.. (2022). Real World Evidence and Clinical Utility of KidneyIntelX on Patients With Early-Stage Diabetic Kidney Disease: Interim Results on Decision Impact and Outcomes. Journal of Primary Care & Community Health. 13. 4267758356–4267758356. 4 indexed citations
11.
Brown, Gordon, Alan W. Partin, Ballentine Carter, et al.. (2021). Predicting high-grade prostate cancer at initial biopsy: clinical performance of the ExoDx (EPI) Prostate Intelliscore test in three independent prospective studies. Prostate Cancer and Prostatic Diseases. 25(2). 296–301. 66 indexed citations
12.
Chan, Lili, Girish N. Nadkarni, James R. McCullough, et al.. (2021). Derivation and validation of a machine learning risk score using biomarker and electronic patient data to predict progression of diabetic kidney disease. Diabetologia. 64(7). 1504–1515. 92 indexed citations
13.
McKiernan, James M., Mikkel Noerholm, Vasisht Tadigotla, et al.. (2020). A urine-based Exosomal gene expression test stratifies risk of high-grade prostate Cancer in men with prior negative prostate biopsy undergoing repeat biopsy. BMC Urology. 20(1). 138–138. 35 indexed citations
14.
Gong, Yixuan, Li Wang, Naomi Alpert, et al.. (2019). Prostate Cancer in World Trade Center Responders Demonstrates Evidence of an Inflammatory Cascade. Molecular Cancer Research. 17(8). 1605–1612. 20 indexed citations
15.
Kyi, Chrisann, Vladimir Roudko, Rachel Lubong Sabado, et al.. (2018). Therapeutic Immune Modulation against Solid Cancers with Intratumoral Poly-ICLC: A Pilot Trial. Clinical Cancer Research. 24(20). 4937–4948. 97 indexed citations
16.
Donovan, Michael & Carlos Cordon‐Cardo. (2016). Implementation of a Precision Pathology Program Focused on Oncology-Based Prognostic and Predictive Outcomes. Molecular Diagnosis & Therapy. 21(2). 115–123. 8 indexed citations
17.
Marín‐Aguilera, Mercedes, Jordi Codony‐Servat, Òscar Reig, et al.. (2014). Epithelial-to-Mesenchymal Transition Mediates Docetaxel Resistance and High Risk of Relapse in Prostate Cancer. Molecular Cancer Therapeutics. 13(5). 1270–1284. 123 indexed citations
18.
Huynh, Jimmy, Paras Garg, Tin Htwe Thin, et al.. (2013). Epigenome-wide differences in pathology-free regions of multiple sclerosis–affected brains. Nature Neuroscience. 17(1). 121–130. 187 indexed citations
19.
Acquaviva, Jaime, Julie Lessard, Huijun Zhu, et al.. (2011). Chronic Activation of Wild-Type Epidermal Growth Factor Receptor and Loss of Cdkn2a Cause Mouse Glioblastoma Formation. Cancer Research. 71(23). 7198–7206. 1 indexed citations
20.

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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