Pavol Mikoláš

489 total citations
18 papers, 251 citations indexed

About

Pavol Mikoláš is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Psychiatry and Mental health. According to data from OpenAlex, Pavol Mikoláš has authored 18 papers receiving a total of 251 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cognitive Neuroscience, 6 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Psychiatry and Mental health. Recurrent topics in Pavol Mikoláš's work include Functional Brain Connectivity Studies (10 papers), Advanced Neuroimaging Techniques and Applications (6 papers) and Advanced MRI Techniques and Applications (3 papers). Pavol Mikoláš is often cited by papers focused on Functional Brain Connectivity Studies (10 papers), Advanced Neuroimaging Techniques and Applications (6 papers) and Advanced MRI Techniques and Applications (3 papers). Pavol Mikoláš collaborates with scholars based in Czechia, Germany and Canada. Pavol Mikoláš's co-authors include Filip Španiel, Tomáš Hájek, Antonín Škoch, Tomáš Melicher, Thomas Frodl, Jaroslav Hlinka, Jiřı́ Horáček, Cyril Höschl, Jaroslav Tintěra and Martin Matějka and has published in prestigious journals such as PLoS ONE, Scientific Reports and The British Journal of Psychiatry.

In The Last Decade

Pavol Mikoláš

17 papers receiving 249 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pavol Mikoláš Czechia 8 142 78 64 45 27 18 251
Mathilde Antoniades United Kingdom 11 185 1.3× 78 1.0× 172 2.7× 45 1.0× 26 1.0× 19 349
Amalia Guerrero‐Pedraza Spain 10 212 1.5× 102 1.3× 111 1.7× 48 1.1× 9 0.3× 26 344
Teresa M. Karrer United States 6 179 1.3× 28 0.4× 44 0.7× 46 1.0× 22 0.8× 8 312
Pasquale Di Carlo Italy 14 136 1.0× 61 0.8× 62 1.0× 24 0.5× 14 0.5× 20 395
Zhongwei Guo China 13 252 1.8× 118 1.5× 121 1.9× 63 1.4× 14 0.5× 32 417
Carolyn McNabb United Kingdom 10 119 0.8× 57 0.7× 50 0.8× 22 0.5× 20 0.7× 18 239
Huan Huang China 11 205 1.4× 99 1.3× 76 1.2× 67 1.5× 19 0.7× 33 375
Anais Harneit Germany 11 244 1.7× 88 1.1× 153 2.4× 72 1.6× 10 0.4× 14 407
Adam Mezher United States 9 211 1.5× 112 1.4× 101 1.6× 37 0.8× 9 0.3× 12 341
Charles Laidi France 10 188 1.3× 97 1.2× 96 1.5× 22 0.5× 17 0.6× 27 311

Countries citing papers authored by Pavol Mikoláš

Since Specialization
Citations

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

Fields of papers citing papers by Pavol Mikoláš

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pavol Mikoláš

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

All Works

18 of 18 papers shown
1.
Wiest, Isabella C., Dyke Ferber, Michael Bauer, et al.. (2024). Detection of suicidality from medical text using privacy-preserving large language models. The British Journal of Psychiatry. 225(6). 532–537. 5 indexed citations
2.
Mikoláš, Pavol, Amirali Vahid, Fabio Bernardoni, et al.. (2022). Training a machine learning classifier to identify ADHD based on real-world clinical data from medical records. Scientific Reports. 12(1). 12934–12934. 21 indexed citations
3.
Mikoláš, Pavol, et al.. (2022). Praktische Aspekte der Ketaminbehandlung – Sicherheit, Kombinationstherapien und Komorbiditäten. Der Nervenarzt. 93(3). 243–253. 1 indexed citations
4.
Mikoláš, Pavol, Leonardo Tozzi, Kelly Doolin, et al.. (2019). Effects of early life adversity and FKBP5 genotype on hippocampal subfields volume in major depression. Journal of Affective Disorders. 252. 152–159. 36 indexed citations
5.
Mikoláš, Pavol, Jaroslav Hlinka, Antonín Škoch, et al.. (2018). Machine learning classification of first-episode schizophrenia spectrum disorders and controls using whole brain white matter fractional anisotropy. BMC Psychiatry. 18(1). 97–97. 34 indexed citations
6.
Mikoláš, Pavol, Jaroslav Hlinka, Antonín Škoch, et al.. (2018). 07-Connectivity of the anterior insula differentiates participants with first-episode schizophrenia spectrum disorders from controls: A machine-learning study. Clinical Neurophysiology. 129(4). e8–e8. 1 indexed citations
7.
Mikoláš, Pavol, Leonardo Tozzi, Kelly Doolin, et al.. (2018). Hippocampal subfields volumes, endocrine stress axis and early life stress in major depressive disorder. European Neuropsychopharmacology. 28. S69–S70. 2 indexed citations
8.
Mikoláš, Pavol. (2018). Improving the diagnosis of first-episode schizophrenia from magnetic resonance imaging using machine learning. Digital Repository (National Repository of Grey Literature). 1 indexed citations
9.
Mikoláš, Pavol, Jaroslav Hlinka, Antonín Škoch, et al.. (2017). Classification of first-episode schizophrenia spectrum disorders and controls from whole brain white matter fractional anisotropy using machine learning. European Psychiatry. 41(S1). S191–S191. 1 indexed citations
10.
Mikoláš, Pavol, Tomáš Melicher, Antonín Škoch, et al.. (2016). Connectivity of the anterior insula differentiates participants with first-episode schizophrenia spectrum disorders from controls: a machine-learning study. Psychological Medicine. 46(13). 2695–2704. 46 indexed citations
11.
Mikoláš, Pavol, Tomáš Melicher, Antonín Škoch, et al.. (2016). Diagnostic classification of patients with first-episode schizophrenia spectrum disorders from resting-fMRI. European Neuropsychopharmacology. 26. S490–S490.
12.
Melicher, Tomáš, Jiřı́ Horáček, Jaroslav Hlinka, et al.. (2015). White matter changes in first episode psychosis and their relation to the size of sample studied: A DTI study. Schizophrenia Research. 162(1-3). 22–28. 44 indexed citations
13.
Španiel, Filip, Jaroslav Tintěra, Ibrahim Ibrahim, et al.. (2015). Altered Neural Correlate of the Self-Agency Experience in First-Episode Schizophrenia-Spectrum Patients: An fMRI Study. Schizophrenia Bulletin. 42(4). 916–925. 26 indexed citations
14.
Horáček, Jiřı́, Pavol Mikoláš, Jaroslav Tintěra, et al.. (2015). Sad mood induction has an opposite effect on amygdala response to emotional stimuli in euthymic patients with bipolar disorder and healthy controls. Journal of Psychiatry and Neuroscience. 40(2). 134–142. 19 indexed citations
15.
Mohr, Penny, et al.. (2014). P.1.k.017 Adult ADHD in a general psychiatric population. European Neuropsychopharmacology. 24. S350–S351. 1 indexed citations
16.
17.
Fajnerová, Iveta, Mabel Rodríguez, Pavol Mikoláš, et al.. (2013). Spatial memory in a virtual arena: Human virtual analogue of the Morris water maze. 186–187. 1 indexed citations
18.
Mikoláš, Pavol, et al.. (2012). Analysis of fMRI time-series by entropy measures.. PubMed. 33(5). 471–6. 4 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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