Michael J. Baine

2.8k total citations
81 papers, 1.5k citations indexed

About

Michael J. Baine is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Michael J. Baine has authored 81 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Oncology, 36 papers in Pulmonary and Respiratory Medicine and 21 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Michael J. Baine's work include Pancreatic and Hepatic Oncology Research (25 papers), Radiomics and Machine Learning in Medical Imaging (15 papers) and Glioma Diagnosis and Treatment (11 papers). Michael J. Baine is often cited by papers focused on Pancreatic and Hepatic Oncology Research (25 papers), Radiomics and Machine Learning in Medical Imaging (15 papers) and Glioma Diagnosis and Treatment (11 papers). Michael J. Baine collaborates with scholars based in United States, China and Austria. Michael J. Baine's co-authors include Chi Lin, Aaron R. Sasson, Surinder K. Batra, Sukhwinder Kaur, Maneesh Jain, Subhankar Chakraborty, Surinder K. Batra, Lynette M. Smith, Kavita Mallya and Jane L. Meza and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Gastroenterology.

In The Last Decade

Michael J. Baine

77 papers receiving 1.4k citations

Peers

Michael J. Baine
Mayu Yunokawa Japan
Yuji Seo Japan
Robert W. Mutter United States
Marie‐Christine Mathieu France
Magdolna Dank Hungary
Hong Ge China
Panagiotis J. Vlachostergios United States
Joyce Sanders Netherlands
Choong‐kun Lee South Korea
Toshi Menju Japan
Mayu Yunokawa Japan
Michael J. Baine
Citations per year, relative to Michael J. Baine Michael J. Baine (= 1×) peers Mayu Yunokawa

Countries citing papers authored by Michael J. Baine

Since Specialization
Citations

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

Fields of papers citing papers by Michael J. Baine

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael J. Baine

This figure shows the co-authorship network connecting the top 25 collaborators of Michael J. Baine. A scholar is included among the top collaborators of Michael J. Baine 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 J. Baine. Michael J. Baine 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.
Kosmacek, Elizabeth A., Michael J. Baine, Arpita Chatterjee, et al.. (2024). Exogenous APN protects normal tissues from radiation-induced oxidative damage and fibrosis in mice and prostate cancer patients with higher levels of APN have less radiation-induced toxicities. Redox Biology. 73. 103219–103219. 9 indexed citations
2.
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Huynh, Linda My, et al.. (2024). Predictive Value of Multiparametric Magnetic Resonance Imaging in Risk Group Stratification of Prostate Adenocarcinoma. Advances in Radiation Oncology. 9(6). 101493–101493.
4.
Huynh, Linda My, et al.. (2023). Multi-Institutional Development and Validation of a Radiomic Model to Predict Prostate Cancer Recurrence Following Radical Prostatectomy. Journal of Clinical Medicine. 12(23). 7322–7322. 8 indexed citations
5.
Wang, Runqiu, Lynette M. Smith, Charles A. Enke, et al.. (2023). Comparison of sequential versus concurrent chemoradiation regimens in non-metastatic muscle-invasive bladder cancer. Radiation Oncology Journal. 41(3). 154–162. 1 indexed citations
6.
Liu, Cassie, Michael J. Baine, Kurt W. Fisher, Jamés O. Armitage, & Charles A. Enke. (2022). Recurrent Mantle Cell Lymphoma Isolated to the Testis After 19-Year Remission: A Case Report and Review of the Literature. Clinical Lymphoma Myeloma & Leukemia. 23(2). e125–e129.
7.
Wong, Jeffrey, Michael J. Baine, Nathan R. Bennion, et al.. (2021). Effects of interobserver and interdisciplinary segmentation variabilities on CT-based radiomics for pancreatic cancer. Scientific Reports. 11(1). 16328–16328. 28 indexed citations
8.
Reames, Bradley N., Kelsey Klute, William A. Hall, et al.. (2021). The timing and design of stereotactic radiotherapy approaches as a part of neoadjuvant therapy in pancreatic cancer: Is it time for change?. Clinical and Translational Radiation Oncology. 28. 124–128. 6 indexed citations
9.
Lin, Chi, Michael J. Baine, Nathan R. Bennion, et al.. (2020). Effect Of Interobserver And Interdisciplinary Segmentation Variability On Radiomic Features For Pancreatic Cancer. International Journal of Radiation Oncology*Biology*Physics. 108(3). e769–e770. 1 indexed citations
10.
Grinnell, Madison, Adams K. Appiah, Michael J. Baine, et al.. (2020). Adjuvant chemotherapy following SBRT for early stage non-small cell lung cancer (NSCLC) in older patients. Journal of Geriatric Oncology. 11(7). 1145–1153. 3 indexed citations
11.
Ernani, Vinicius, Adams K. Appiah, Michael J. Baine, Lynette M. Smith, & Apar Kishor Ganti. (2020). The impact of histology in the outcomes of patients with early-stage non-small cell lung cancer (NSCLC) treated with stereotactic body radiation therapy (SBRT) and adjuvant chemotherapy. Cancer Treatment and Research Communications. 24. 100197–100197. 2 indexed citations
12.
Tormoen, Garth W., Tiffany C. Blair, Shelly Bambina, et al.. (2020). Targeting MerTK Enhances Adaptive Immune Responses After Radiation Therapy. International Journal of Radiation Oncology*Biology*Physics. 108(1). 93–103. 23 indexed citations
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Sleightholm, Richard, et al.. (2020). Efficacy of sequential radiation and chemotherapy in treating glioblastoma with poor performance status. Journal of Neuro-Oncology. 147(1). 91–95. 3 indexed citations
15.
Du, Qian, Michael J. Baine, Xiaoying Liang, et al.. (2019). Radiomic feature stability across 4D respiratory phases and its impact on lung tumor prognosis prediction. PLoS ONE. 14(5). e0216480–e0216480. 33 indexed citations
16.
Neilsen, Beth K., et al.. (2019). A 47-year-old woman with nuclear protein in testis midline carcinoma masquerading as a sinus infection: a case report and review of the literature. Journal of Medical Case Reports. 13(1). 57–57. 7 indexed citations
17.
Baine, Michael J., Vivek Verma, Caitlin A. Schonewolf, Chi Lin, & Charles B. Simone. (2018). Histology significantly affects recurrence and survival following SBRT for early stage non-small cell lung cancer. Lung Cancer. 118. 20–26. 40 indexed citations
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Kaur, Sukhwinder, Neil Sharma, Shiv Ram Krishn, et al.. (2013). MUC4-Mediated Regulation of Acute Phase Protein Lipocalin 2 through HER2/AKT/NF-κB Signaling in Pancreatic Cancer. Clinical Cancer Research. 20(3). 688–700. 36 indexed citations
20.
Baine, Michael J., et al.. (2011). Marital Status and Survival in Pancreatic Cancer Patients: A SEER Based Analysis. PLoS ONE. 6(6). e21052–e21052. 95 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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