Michael A. Jacobs

15.7k total citations · 1 hit paper
190 papers, 10.9k citations indexed

About

Michael A. Jacobs is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology and Surgery. According to data from OpenAlex, Michael A. Jacobs has authored 190 papers receiving a total of 10.9k indexed citations (citations by other indexed papers that have themselves been cited), including 94 papers in Radiology, Nuclear Medicine and Imaging, 37 papers in Molecular Biology and 31 papers in Surgery. Recurrent topics in Michael A. Jacobs's work include MRI in cancer diagnosis (58 papers), Advanced MRI Techniques and Applications (46 papers) and Radiomics and Machine Learning in Medical Imaging (37 papers). Michael A. Jacobs is often cited by papers focused on MRI in cancer diagnosis (58 papers), Advanced MRI Techniques and Applications (46 papers) and Radiomics and Machine Learning in Medical Imaging (37 papers). Michael A. Jacobs collaborates with scholars based in United States, Iran and Netherlands. Michael A. Jacobs's co-authors include David A. Bluemke, Vishwa S. Parekh, Peter B. Barker, Katarzyna J. Macura, Zaver M. Bhujwalla, Rajinder Kaul, Laura M. Fayad, Colin Manoil, Ihab R. Kamel and Ronald Ouwerkerk and has published in prestigious journals such as Science, Chemical Reviews and Proceedings of the National Academy of Sciences.

In The Last Decade

Michael A. Jacobs

184 papers receiving 10.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Comprehensive transposon mutant library of Pseudomonas aeruginosa

2003 932 citations Michael A. Jacobs, Eric Haugen et al. Proceedings of the National Academy of Sciences profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael A. Jacobs United States	58	4.0k	2.8k	1.6k	1.5k	1.3k	190	10.9k
Rolf Fimmers Germany	67	2.7k 0.7×	2.4k 0.9×	1.9k 1.2×	2.0k 1.4×	1.6k 1.2×	350	14.4k
Kwang Pyo Kim South Korea	61	3.3k 0.8×	6.6k 2.4×	1.3k 0.8×	1.4k 1.0×	625 0.5×	316	15.3k
Leonore A. Herzenberg United States	81	2.2k 0.6×	6.2k 2.2×	854 0.5×	625 0.4×	1.2k 0.9×	202	20.1k
James Lee United States	65	993 0.3×	6.0k 2.1×	1.1k 0.7×	2.5k 1.7×	2.2k 1.7×	258	17.0k
Liang Wang China	61	1.0k 0.3×	8.1k 2.9×	1.9k 1.2×	1.9k 1.3×	806 0.6×	795	16.6k
Douglas H. Smith United States	90	2.6k 0.7×	9.5k 3.4×	1.7k 1.1×	755 0.5×	1.2k 0.9×	284	28.8k
Xuan Zhang China	65	908 0.2×	7.9k 2.8×	1.9k 1.2×	1.9k 1.3×	1.2k 0.9×	868	22.7k
Markus Loeffler Germany	71	1.5k 0.4×	4.3k 1.5×	2.3k 1.4×	1.1k 0.8×	1.7k 1.3×	394	18.6k
David J. Wilson United States	54	4.1k 1.0×	1.6k 0.6×	700 0.4×	3.0k 2.1×	429 0.3×	278	12.5k
Kazuhiko Yamamoto Japan	78	2.0k 0.5×	5.5k 2.0×	1.7k 1.0×	1.4k 1.0×	1.7k 1.4×	772	25.1k

Countries citing papers authored by Michael A. Jacobs

Since Specialization

Citations

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

Fields of papers citing papers by Michael A. Jacobs

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael A. Jacobs

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Kamali, Arash, Atif Ali, Andrés González‐Gutiérrez, et al.. (2025). Direct parieto-occipital connectivity of the amygdala via the parahippocampal segment of the cingulum bundle. The Neuroradiology Journal. 39(1). 70–77. 1 indexed citations

Narayana, Ponnada A., et al.. (2024). Automatic Active Lesion Tracking in Multiple Sclerosis Using Unsupervised Machine Learning. Diagnostics. 14(6). 632–632. 3 indexed citations

Jacobs, Michael A., Jay‐Jiguang Zhu, Yoshua Esquenazi, et al.. (2024). The Use of Apparent Diffusion Coefficient Values for Differentiating Bevacizumab-Related Cytotoxicity from Tumor Recurrence and Radiation Necrosis in Glioblastoma. Cancers. 16(13). 2440–2440. 1 indexed citations

Sagreiya, Hersh, Michael A. Jacobs, & Alireza Akhbardeh. (2023). Automated Lung Ultrasound Pulmonary Disease Quantification Using an Unsupervised Machine Learning Technique for COVID-19. Diagnostics. 13(16). 2692–2692. 2 indexed citations

Tulpan, Dan, et al.. (2023). Review: When worlds collide – poultry modeling in the ‘Big Data’ era. animal. 17. 100874–100874. 7 indexed citations

Parekh, Vishwa S., Xuguang Chen, Kristin J. Redmond, et al.. (2023). A Multidimensional Connectomics- and Radiomics-Based Advanced Machine-Learning Framework to Distinguish Radiation Necrosis from True Progression in Brain Metastases. Cancers. 15(16). 4113–4113. 6 indexed citations

Chen, Xuguang, Vishwa S. Parekh, Luke Peng, et al.. (2021). Multiparametric radiomic tissue signature and machine learning for distinguishing radiation necrosis from tumor progression after stereotactic radiosurgery. Neuro-Oncology Advances. 3(1). vdab150–vdab150. 14 indexed citations

Chen, X., Vishwa S. Parekh, Luke Peng, et al.. (2020). External Validation Of A Radiomics-Based Machine Learning Model For Distinguishing Radiation Necrosis From Progression Of Brain Metastases Treated With Stereotactic Radiosurgery. International Journal of Radiation Oncology*Biology*Physics. 108(3). e722–e723. 2 indexed citations

Blakeley, Jaishri O., Xiaobu Ye, Dan G. Duda, et al.. (2016). Efficacy and Biomarker Study of Bevacizumab for Hearing Loss Resulting From Neurofibromatosis Type 2–Associated Vestibular Schwannomas. Journal of Clinical Oncology. 34(14). 1669–1675. 86 indexed citations

10.

Salipante, Stephen J., Dhruba J. SenGupta, Christopher Rosenthal, et al.. (2013). Rapid 16S rRNA Next-Generation Sequencing of Polymicrobial Clinical Samples for Diagnosis of Complex Bacterial Infections. PLoS ONE. 8(5). e65226–e65226. 174 indexed citations

11.

Hayden, Hillary S., Regina Lim, M. Brittnacher, et al.. (2012). Evolution of Burkholderia pseudomallei in Recurrent Melioidosis. PLoS ONE. 7(5). e36507–e36507. 93 indexed citations

12.

Jacobs, Michael A., et al.. (2012). Postresurfacing Periprosthetic Femoral Neck Fractures: Nonoperative Treatment. Orthopedics. 35(5). e732–6. 3 indexed citations

13.

Jacobs, Michael A., Ronald Ouwerkerk, Ihab R. Kamel, et al.. (2009). Proton, diffusion‐weighted imaging, and sodium (²³Na) MRI of uterine leiomyomata after MR‐guided high‐intensity focused ultrasound: A preliminary study. Journal of Magnetic Resonance Imaging. 29(3). 649–656. 33 indexed citations

14.

Hayden, Hillary S., Will Gillett, Channakhone Saenphimmachak, et al.. (2008). Large-insert genome analysis technology detects structural variation in Pseudomonas aeruginosa clinical strains from cystic fibrosis patients. Genomics. 91(6). 530–537. 25 indexed citations

15.

Giddens, Stephen R., Robert W. Jackson, Christina D. Moon, et al.. (2007). Mutational activation of niche-specific genes provides insight into regulatory networks and bacterial function in a complex environment. Proceedings of the National Academy of Sciences. 104(46). 18247–18252. 66 indexed citations

16.

Fayad, Laura M., Peter B. Barker, Michael A. Jacobs, et al.. (2007). Characterization of Musculoskeletal Lesions on 3-T Proton MR Spectroscopy. American Journal of Roentgenology. 188(6). 1513–1520. 50 indexed citations

17.

Harkey, Michael A., Rajinder Kaul, Michael A. Jacobs, et al.. (2007). Multiarm High-Throughput Integration Site Detection: Limitations of LAM-PCR Technology and Optimization for Clonal Analysis. Stem Cells and Development. 16(3). 381–392. 29 indexed citations

18.

Beard, Brian C., David Dickerson, James Fletcher, et al.. (2007). Comparison of HIV-derived Lentiviral and MLV-based Gammaretroviral Vector Integration Sites in Primate Repopulating Cells. Molecular Therapy. 15(7). 1356–1365. 90 indexed citations

19.

Wu, Licheng, Oscar Estrada, Olga Zaborina, et al.. (2005). Recognition of Host Immune Activation by Pseudomonas aeruginosa. Science. 309(5735). 774–777. 256 indexed citations

20.

Rohlfing, Torsten, Calvin R. Maurer, David A. Bluemke, & Michael A. Jacobs. (2003). Volume-preserving nonrigid registration of MR breast images using free-form deformation with an incompressibility constraint. IEEE Transactions on Medical Imaging. 22(6). 730–741. 302 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.

Explore authors with similar magnitude of impact