Ivo D. Dinov

10.6k total citations
197 papers, 7.2k citations indexed

About

Ivo D. Dinov is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Ivo D. Dinov has authored 197 papers receiving a total of 7.2k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Radiology, Nuclear Medicine and Imaging, 42 papers in Computer Vision and Pattern Recognition and 41 papers in Cognitive Neuroscience. Recurrent topics in Ivo D. Dinov's work include Functional Brain Connectivity Studies (35 papers), Advanced Neuroimaging Techniques and Applications (28 papers) and Medical Image Segmentation Techniques (28 papers). Ivo D. Dinov is often cited by papers focused on Functional Brain Connectivity Studies (35 papers), Advanced Neuroimaging Techniques and Applications (28 papers) and Medical Image Segmentation Techniques (28 papers). Ivo D. Dinov collaborates with scholars based in United States, China and France. Ivo D. Dinov's co-authors include Arthur W. Toga, Paul M. Thompson, Jeffrey L. Cummings, Rebecca A. Dutton, Liana G. Apostolova, Yonggang Shi, Nicolas V. Christou, Elizabeth R. Sowell, Kiralee M. Hayashi and Arthur W. Toga and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Neuroscience.

In The Last Decade

Ivo D. Dinov

194 papers receiving 6.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ivo D. Dinov United States 46 1.9k 1.8k 1.4k 1.0k 902 197 7.2k
Marc Modat United Kingdom 44 1.2k 0.6× 3.4k 1.9× 1.3k 0.9× 1.0k 1.0× 1.5k 1.6× 178 7.1k
Vladimir Fonov Canada 39 2.0k 1.1× 2.5k 1.4× 1.1k 0.8× 712 0.7× 1.1k 1.3× 146 6.8k
William R. Crum United Kingdom 36 1.5k 0.8× 2.2k 1.2× 1.5k 1.1× 1.2k 1.1× 1.1k 1.3× 97 5.9k
Olivier Colliot France 39 1.8k 0.9× 1.6k 0.9× 2.3k 1.7× 1.4k 1.4× 1.3k 1.4× 156 6.5k
Daniel S. Marcus United States 23 1.7k 0.9× 1.5k 0.8× 1.1k 0.8× 663 0.6× 828 0.9× 60 4.4k
Koen Van Leemput United States 36 1.5k 0.8× 2.3k 1.3× 873 0.6× 555 0.5× 2.3k 2.6× 104 6.6k
Albert Montillo United States 19 3.6k 1.9× 2.6k 1.5× 1.9k 1.4× 911 0.9× 789 0.9× 59 7.6k
Rolf A. Heckemann United Kingdom 35 936 0.5× 1.8k 1.0× 1.0k 0.7× 489 0.5× 1.5k 1.7× 92 5.6k
Arno Klein United States 20 3.1k 1.6× 3.2k 1.8× 863 0.6× 568 0.5× 1.2k 1.4× 52 7.7k
Lei Wang United States 51 3.3k 1.7× 2.4k 1.4× 2.6k 1.9× 1.5k 1.5× 561 0.6× 293 8.8k

Countries citing papers authored by Ivo D. Dinov

Since Specialization
Citations

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

Fields of papers citing papers by Ivo D. Dinov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ivo D. Dinov. 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 Ivo D. Dinov. The network helps show where Ivo D. Dinov may publish in the future.

Co-authorship network of co-authors of Ivo D. Dinov

This figure shows the co-authorship network connecting the top 25 collaborators of Ivo D. Dinov. A scholar is included among the top collaborators of Ivo D. Dinov 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 Ivo D. Dinov. Ivo D. Dinov 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.
Niraula, Dipesh, Jionghua Jin, Ivo D. Dinov, et al.. (2023). A clinical decision support system for AI-assisted decision-making in response-adaptive radiotherapy (ARCliDS). Scientific Reports. 13(1). 5279–5279. 27 indexed citations
2.
Dinov, Ivo D.. (2023). Data Science and Predictive Analytics. 3 indexed citations
3.
Rahman, Hanif Abdul, et al.. (2023). Machine Learning-Based Prediction of Mental Well-Being Using Health Behavior Data from University Students. Bioengineering. 10(5). 575–575. 17 indexed citations
4.
Zhou, Nina, et al.. (2022). Optimal dynamic treatment regime estimation using information extraction from unstructured clinical text. Biometrical Journal. 64(4). 805–817. 4 indexed citations
5.
Kalinin, Alexandr A., Alex Ade, Walter Meixner, et al.. (2021). Valproic acid-induced changes of 4D nuclear morphology in astrocyte cells. Molecular Biology of the Cell. 32(18). 1624–1633. 9 indexed citations
6.
Katapodi, Maria C., Chang Ming, Laurel Northouse, et al.. (2020). Genetic Testing and Surveillance of Young Breast Cancer Survivors and Blood Relatives: A Cluster Randomized Trial. Cancers. 12(9). 2526–2526. 4 indexed citations
7.
Dinov, Ivo D.. (2020). Modernizing the Methods and Analytics Curricula for Health Science Doctoral Programs. Frontiers in Public Health. 8. 22–22. 5 indexed citations
8.
Zhao, Lu, William Matloff, Kaida Ning, et al.. (2018). Age-Related Differences in Brain Morphology and the Modifiers in Middle-Aged and Older Adults. Cerebral Cortex. 29(10). 4169–4193. 48 indexed citations
9.
Zheng, Gen, Alexandr A. Kalinin, Ivo D. Dinov, et al.. (2018). Hypothesis: Caco‐2 cell rotational 3D mechanogenomic turing patterns have clinical implications to colon crypts. Journal of Cellular and Molecular Medicine. 22(12). 6380–6385. 4 indexed citations
10.
Amiri, Saeid & Ivo D. Dinov. (2016). Comparison of genomic data via statistical distribution. Journal of Theoretical Biology. 407. 318–327. 4 indexed citations
11.
Chard, Kyle, Mike D’Arcy, Ben Heavner, et al.. (2016). I'll take that to go: Big data bags and minimal identifiers for exchange of large, complex datasets. Research Explorer (The University of Manchester). 319–328. 28 indexed citations
12.
Toga, Arthur W., Ian Foster, Carl Kesselman, et al.. (2015). Big biomedical data as the key resource for discovery science. Journal of the American Medical Informatics Association. 22(6). 1126–1131. 59 indexed citations
13.
Garijo, Daniel, Óscar Corcho, Yolanda Gil, et al.. (2014). FragFlow Automated Fragment Detection in Scientific Workflows. UPM Digital Archive (Technical University of Madrid). 281–289. 9 indexed citations
14.
Labus, Jennifer S., Ivo D. Dinov, Zhiguo Jiang, et al.. (2013). Irritable bowel syndrome in female patients is associated with alterations in structural brain networks. Pain. 155(1). 137–149. 127 indexed citations
15.
Dinov, Ivo D.. (2013). An Empirical Study on Economic Prosperity and Peace. 1 indexed citations
16.
Joshi, Shantanu H., Antonio Marquina, Stanley Osher, et al.. (2011). Fast edge-filtered image upsampling. PubMed. 26. 1165–1168. 5 indexed citations
17.
Liu, Xiuwen, Yonggang Shi, Ivo D. Dinov, & Washington Mio. (2010). A Computational Model of Multidimensional Shape. International Journal of Computer Vision. 89(1). 69–83. 10 indexed citations
18.
Xu, Yuan, Daniel J. Valentino, I Scher, et al.. (2008). Age effects on hippocampal structural changes in old men: The HAAS. NeuroImage. 40(3). 1003–1015. 24 indexed citations
19.
Apostolova, Liana G., Ivo D. Dinov, Rebecca A. Dutton, et al.. (2006). 3D comparison of hippocampal atrophy in amnestic mild cognitive impairment and Alzheimer's disease. Brain. 129(11). 2867–2873. 207 indexed citations
20.
Dinov, Ivo D., et al.. (2006). Assessment of the Pedagogical Utilization of the Statistics Online Computational Resource in Introductory Probability Courses: a Quasi-Experiment. eScholarship (California Digital Library). 1 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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