Daniel S. Reich

29.6k total citations · 9 hit papers
295 papers, 16.2k citations indexed

About

Daniel S. Reich is a scholar working on Pathology and Forensic Medicine, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Daniel S. Reich has authored 295 papers receiving a total of 16.2k indexed citations (citations by other indexed papers that have themselves been cited), including 158 papers in Pathology and Forensic Medicine, 115 papers in Radiology, Nuclear Medicine and Imaging and 39 papers in Molecular Biology. Recurrent topics in Daniel S. Reich's work include Multiple Sclerosis Research Studies (153 papers), Advanced Neuroimaging Techniques and Applications (67 papers) and Advanced MRI Techniques and Applications (41 papers). Daniel S. Reich is often cited by papers focused on Multiple Sclerosis Research Studies (153 papers), Advanced Neuroimaging Techniques and Applications (67 papers) and Advanced MRI Techniques and Applications (41 papers). Daniel S. Reich collaborates with scholars based in United States, Italy and Canada. Daniel S. Reich's co-authors include Peter A. Calabresi, Claudia F. Lucchinetti, Pascal Sati, Martina Absinta, Jonathan D. Victor, Ciprian M. Crainiceanu, Irene Cortese, Ferenc Mechler, Peter C.M. van Zijl and Govind Nair and has published in prestigious journals such as Nature, Science and New England Journal of Medicine.

In The Last Decade

Daniel S. Reich

284 papers receiving 16.0k citations

Hit Papers

Multiple Sclerosis 2007 2026 2013 2019 2018 2007 2016 2017 2021 500 1000 1.5k

Author Peers

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

Author Last Decade Papers Cites
Daniel S. Reich 6.9k 4.9k 2.8k 2.2k 2.0k 295 16.2k
Jeroen J.G. Geurts 11.5k 1.7× 4.3k 0.9× 3.3k 1.2× 2.4k 1.1× 3.0k 1.5× 234 16.7k
Tarek Yousry 5.1k 0.7× 4.1k 0.8× 5.7k 2.1× 1.7k 0.8× 2.6k 1.3× 332 16.3k
Anne H. Cross 6.6k 1.0× 8.0k 1.6× 3.3k 1.2× 2.6k 1.2× 2.6k 1.3× 253 20.3k
Giancarlo Comi 10.6k 1.5× 3.6k 0.7× 3.9k 1.4× 2.1k 1.0× 1.1k 0.5× 233 14.4k
Olga Ciccarelli 9.6k 1.4× 10.6k 2.2× 5.0k 1.8× 1.9k 0.9× 2.0k 1.0× 272 22.4k
Robert Zivadinov 12.7k 1.9× 3.0k 0.6× 5.7k 2.1× 2.2k 1.0× 2.1k 1.0× 581 19.4k
Rohit Bakshi 9.2k 1.3× 2.5k 0.5× 3.8k 1.4× 2.0k 0.9× 1.4k 0.7× 259 14.2k
Robert I. Grossman 5.6k 0.8× 7.2k 1.5× 6.4k 2.3× 1.9k 0.9× 842 0.4× 285 18.6k
Àlex Rovira 8.4k 1.2× 3.2k 0.7× 5.0k 1.8× 1.8k 0.8× 1.5k 0.8× 408 16.3k
Bernard M.J. Uitdehaag 12.1k 1.8× 2.3k 0.5× 4.1k 1.5× 2.5k 1.2× 1.6k 0.8× 457 18.7k

Countries citing papers authored by Daniel S. Reich

Since Specialization
Citations

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

Fields of papers citing papers by Daniel S. Reich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel S. Reich. 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 Daniel S. Reich. The network helps show where Daniel S. Reich may publish in the future.

Co-authorship network of co-authors of Daniel S. Reich

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel S. Reich. A scholar is included among the top collaborators of Daniel S. Reich 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 Daniel S. Reich. Daniel S. Reich 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.
Hemond, Christopher C., et al.. (2025). Paramagnetic rim lesions are highly specific for multiple sclerosis in real-world data. Brain Communications. 7(3). fcaf211–fcaf211. 1 indexed citations
2.
Rosa, Francesco La, Amit Kumar Kohli, Pietro Maggi, et al.. (2025). A Novel Convolutional Neural Network for Automated Multiple Sclerosis Brain Lesion Segmentation. Journal of Neuroimaging. 35(5). e70085–e70085.
3.
Garton, Thomas, Matthew D. Smith, Marjan Gharagozloo, et al.. (2025). Myeloid lineage C3 induces reactive gliosis and neuronal stress during CNS inflammation. Nature Communications. 16(1). 3481–3481. 4 indexed citations
4.
Smyth, Leon, Steffen E. Storck, Benjamin A. Plog, et al.. (2025). Amyloidosis of bridging veins is a pathologic feature of Alzheimer’s disease. The Journal of Experimental Medicine. 223(2). 2 indexed citations
5.
Pedrini, Edoardo, Céline Bugli, Halil Yıldız, et al.. (2024). Central Vein Sign, Cortical Lesions, and Paramagnetic Rim Lesions for the Diagnostic and Prognostic Workup of Multiple Sclerosis. Neurology Neuroimmunology & Neuroinflammation. 11(4). e200253–e200253. 20 indexed citations
6.
Fagiani, Francesca, Edoardo Pedrini, Stefano Taverna, et al.. (2024). A glia-enriched stem cell 3D model of the human brain mimics the glial-immune neurodegenerative phenotypes of multiple sclerosis. Cell Reports Medicine. 5(8). 101680–101680. 9 indexed citations
7.
Okar, Serhat V., Francesca Fagiani, Martina Absinta, & Daniel S. Reich. (2024). Imaging of brain barrier inflammation and brain fluid drainage in human neurological diseases. Cellular and Molecular Life Sciences. 81(1). 31–31. 8 indexed citations
8.
O’Donnell, Carly M., Mark A. Elliott, Shahamat Tauhid, et al.. (2023). Intersite brain MRI volumetric biases persist even in a harmonized multisubject study of multiple sclerosis. Journal of Neuroimaging. 33(6). 941–952. 6 indexed citations
9.
Tsagkas, Charidimos, et al.. (2023). Pseudo-Label Assisted nnU-Net enables automatic segmentation of 7T MRI from a single acquisition. SHILAP Revista de lepidopterología. 2. 1252261–1252261. 1 indexed citations
10.
Hemond, Christopher C., Jonggyu Baek, Carolina Ionete, & Daniel S. Reich. (2022). Paramagnetic rim lesions are associated with pathogenic CSF profiles and worse clinical status in multiple sclerosis: A retrospective cross-sectional study. Multiple Sclerosis Journal. 28(13). 2046–2056. 28 indexed citations
11.
Absinta, Martina, Dragan Maric, Marjan Gharagozloo, et al.. (2021). A lymphocyte–microglia–astrocyte axis in chronic active multiple sclerosis. Nature. 597(7878). 709–714. 445 indexed citations breakdown →
12.
Guehl, Nicolas J., Karla M. Ramos‐Torres, Clas Linnman, et al.. (2020). Evaluation of the potassium channel tracer [ 18 F]3F4AP in rhesus macaques. Journal of Cerebral Blood Flow & Metabolism. 41(7). 1721–1733. 22 indexed citations
13.
Nair, Govind, Sonya Steele, Erin Beck, et al.. (2020). Manganese-Enhanced MRI in Patients with Multiple Sclerosis. American Journal of Neuroradiology. 41(9). 1569–1576. 5 indexed citations
14.
Nair, Govind, Stephen Dodd, Seung-Kwon Ha, Alan P. Koretsky, & Daniel S. Reich. (2020). Ex vivo MR microscopy of a human brain with multiple sclerosis: Visualizing individual cells in tissue using intrinsic iron. NeuroImage. 223. 117285–117285. 8 indexed citations
15.
Sotirchos, Elias S., Blake E. Dewey, Kathryn C. Fitzgerald, et al.. (2019). Effect of disease-modifying therapies on subcortical gray matter atrophy in multiple sclerosis. Multiple Sclerosis Journal. 26(3). 312–321. 30 indexed citations
16.
Dworkin, Jordan D., Kristin A. Linn, İpek Oğuz, et al.. (2018). An Automated Statistical Technique for Counting Distinct Multiple Sclerosis Lesions. American Journal of Neuroradiology. 39(4). 626–633. 27 indexed citations
17.
Beck, Erin, Pascal Sati, Varun Sethi, et al.. (2018). Improved Visualization of Cortical Lesions in Multiple Sclerosis Using 7T MP2RAGE. American Journal of Neuroradiology. 39(3). 459–466. 57 indexed citations
18.
Luciano, Nicholas J., Pascal Sati, Govind Nair, et al.. (2016). Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning. Journal of Visualized Experiments. 20 indexed citations
19.
Luciano, Nicholas J., Pascal Sati, Govind Nair, et al.. (2016). Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning. Journal of Visualized Experiments. 4 indexed citations
20.
Espinel-Ingroff, Ana, et al.. (1995). Fluconazole for Refractory Oropharyngeal Candidiasis in AIDS Patients. Aids Patient Care. 9(2). 56–59. 2 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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