Maja Ukmar

2.7k total citations
69 papers, 2.1k citations indexed

About

Maja Ukmar is a scholar working on Epidemiology, Neurology and Pathology and Forensic Medicine. According to data from OpenAlex, Maja Ukmar has authored 69 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Epidemiology, 17 papers in Neurology and 16 papers in Pathology and Forensic Medicine. Recurrent topics in Maja Ukmar's work include Multiple Sclerosis Research Studies (13 papers), Acute Ischemic Stroke Management (12 papers) and Traumatic Brain Injury and Neurovascular Disturbances (9 papers). Maja Ukmar is often cited by papers focused on Multiple Sclerosis Research Studies (13 papers), Acute Ischemic Stroke Management (12 papers) and Traumatic Brain Injury and Neurovascular Disturbances (9 papers). Maja Ukmar collaborates with scholars based in Italy, United States and Germany. Maja Ukmar's co-authors include Marino Zorzon, Giuseppe Cazzato, Robert Zivadinov, Davide Nasuelli, Raffaella I. Rumiati, Roberto De Masi, Roberto Pozzi Mucelli, A. Grop, Alessio Bratina and Maria Assunta Cova and has published in prestigious journals such as Brain, Neurology and Scientific Reports.

In The Last Decade

Maja Ukmar

65 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Maja Ukmar Italy 26 834 444 425 345 315 69 2.1k
Flavia Mattioli Italy 29 1.1k 1.4× 696 1.6× 687 1.6× 111 0.3× 158 0.5× 63 2.4k
David I. Kaufman United States 26 1.2k 1.4× 402 0.9× 976 2.3× 60 0.2× 210 0.7× 61 2.9k
Ugo Nocentini Italy 25 869 1.0× 921 2.1× 529 1.2× 71 0.2× 391 1.2× 89 2.8k
C. Mottolèse France 31 201 0.2× 673 1.5× 1.3k 3.1× 286 0.8× 151 0.5× 195 3.8k
Mauro Bergui Italy 28 727 0.9× 313 0.7× 992 2.3× 42 0.1× 186 0.6× 107 2.5k
Andrea Tacchino Italy 25 882 1.1× 445 1.0× 394 0.9× 114 0.3× 159 0.5× 110 1.9k
K. Wessel Germany 18 280 0.3× 450 1.0× 779 1.8× 108 0.3× 154 0.5× 58 2.2k
Danielle Ibarrola France 25 740 0.9× 602 1.4× 330 0.8× 55 0.2× 669 2.1× 52 2.1k
Kathleen M. Zackowski United States 25 962 1.2× 383 0.9× 464 1.1× 51 0.1× 431 1.4× 58 2.3k
Beate Schoch Germany 30 233 0.3× 529 1.2× 882 2.1× 133 0.4× 220 0.7× 59 2.4k

Countries citing papers authored by Maja Ukmar

Since Specialization
Citations

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

Fields of papers citing papers by Maja Ukmar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maja Ukmar

This figure shows the co-authorship network connecting the top 25 collaborators of Maja Ukmar. A scholar is included among the top collaborators of Maja Ukmar 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 Maja Ukmar. Maja Ukmar 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.
2.
Radin, E.L., et al.. (2024). MRI-based assessment of the mylohyoid muscle in oral squamous cell carcinoma, a 7-point scoring method. European Radiology. 35(4). 2065–2073. 1 indexed citations
3.
Dinoto, Alessandro, Miloš Ajčević, Franca Dore, et al.. (2021). ASL MRI and 18F-FDG-PET in autoimmune limbic encephalitis: clues from two paradigmatic cases. Neurological Sciences. 42(8). 3423–3425. 8 indexed citations
4.
Ajčević, Miloš, Giovanni Furlanis, Aleksandar Miladinović, et al.. (2021). Early EEG Alterations Correlate with CTP Hypoperfused Volumes and Neurological Deficit: A Wireless EEG Study in Hyper-Acute Ischemic Stroke. Annals of Biomedical Engineering. 49(9). 2150–2158. 28 indexed citations
5.
Granato, Antonio, et al.. (2020). A novel computed tomography perfusion-based quantitative tool for evaluation of perfusional abnormalities in migrainous aura stroke mimic. Neurological Sciences. 41(11). 3321–3328. 12 indexed citations
6.
Ajčević, Miloš, Giovanni Furlanis, Alex Buoite Stella, et al.. (2020). A CT perfusion based model predicts outcome in wake-up stroke patients treated with recombinant tissue plasminogen activator. Physiological Measurement. 41(7). 75011–75011. 17 indexed citations
7.
Mengotti, Paola, Corrado Corradi‐Dell’Acqua, Gioia A. L. Negri, et al.. (2013). Selective imitation impairments differentially interact with language processing. Brain. 136(8). 2602–2618. 69 indexed citations
8.
Cavallaro, Marco, et al.. (2013). Magnetic resonance urography vs computed tomography urography in the evaluation of patients with haematuria. La radiologia medica. 118(7). 1184–1198. 12 indexed citations
9.
Ukmar, Maja, et al.. (2009). Dependence of the fractional anisotropy in cervical spine from the number of diffusion gradients, repeated acquisition and voxel size. Magnetic Resonance Imaging. 28(1). 70–76. 35 indexed citations
10.
Zivadinov, Robert, Laura Uxa, Alessio Bratina, et al.. (2007). HLA‐DRB1*1501, ‐DQB1*0301, ‐DQB1*0302, ‐DQB1*0602, and ‐DQB1*0603 Alleles are Associated With More Severe Disease Outcome on Mri in Patients With Multiple Sclerosis. International review of neurobiology. 79. 521–535. 62 indexed citations
11.
Ukmar, Maja, Rita Moretti, G. Garbin, et al.. (2006). Functional MRI in the assessment of cortical activation in subjects with Parkinson’s disease. La radiologia medica. 111(1). 104–115. 8 indexed citations
12.
Zivadinov, Robert, Davide Nasuelli, Maria Antonietta Tommasi, et al.. (2006). Positivity of cytomegalovirus antibodies predicts a better clinical and radiological outcome in multiple sclerosis patients. Neurological Research. 28(3). 262–269. 45 indexed citations
13.
Mosconi, Elisa, et al.. (2003). Detection of liver metastases by pulse inversion harmonic imaging with Levovist in comparison to conventional ultrasound and with magnetic resonance imaging (MRI) with Gd-BOPTA as reference procedure. European Radiology. 13. 365–365. 2 indexed citations
14.
Zorzon, Marino, Robert Zivadinov, Davide Nasuelli, et al.. (2002). Depressive symptoms and MRI changes in multiple sclerosis. European Journal of Neurology. 9(5). 491–496. 58 indexed citations
15.
Moretti, Rita, Paola Torre, Rodolfo M. Antonello, et al.. (2002). Learned movements in a left-handed pianist: an f-MRI evaluation. Journal of Clinical Neuroscience. 9(6). 680–684. 4 indexed citations
16.
Moretti, Rita, Paola Torre, Rodolfo M. Antonello, et al.. (2001). Valutazione con Risonanza Magnetica Funzionale dell'attivazione corticale durante compiti motori fini in soggetti con degenerazione cortico-basale. 11(3). 73–79.
17.
Zorzon, Marino, Roberto De Masi, Davide Nasuelli, et al.. (2001). Depression and anxiety in multiple sclerosis. A clinical and MRI study in 95 subjects. Journal of Neurology. 248(5). 416–421. 180 indexed citations
18.
Zivadinov, Robert, Roberto De Masi, Davide Nasuelli, et al.. (2001). MRI techniques and cognitive impairment in the early phase of relapsing-remitting multiple sclerosis. Neuroradiology. 43(4). 272–278. 99 indexed citations
19.
Quaia, Emilio, Michele Bertolotto, Martina Locatelli, & Maja Ukmar. (2000). Detection of liver metastases with pulse inversion harmonic imaging. Electronic Commerce Research. 26. -–-. 1 indexed citations
20.
Magnaldi, S, et al.. (1997). Assessment of pituitary microadenomas: Comparison between 2D and 3D MR sequences. Magnetic Resonance Imaging. 15(1). 21–27. 10 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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