David Popovic

924 total citations
16 papers, 235 citations indexed

About

David Popovic is a scholar working on Psychiatry and Mental health, Clinical Psychology and Cognitive Neuroscience. According to data from OpenAlex, David Popovic has authored 16 papers receiving a total of 235 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Psychiatry and Mental health, 4 papers in Clinical Psychology and 3 papers in Cognitive Neuroscience. Recurrent topics in David Popovic's work include Schizophrenia research and treatment (4 papers), Functional Brain Connectivity Studies (3 papers) and Psychosomatic Disorders and Their Treatments (2 papers). David Popovic is often cited by papers focused on Schizophrenia research and treatment (4 papers), Functional Brain Connectivity Studies (3 papers) and Psychosomatic Disorders and Their Treatments (2 papers). David Popovic collaborates with scholars based in Germany, Brazil and United Kingdom. David Popovic's co-authors include Peter Falkai, Andrea Schmitt, Berend Malchow, Sergi Papiol, Nikolaos Koutsouleris, Lalit Kaurani, Fanny Senner, André Fischer, Thomas G. Schulze and Séverine Trannoy and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Biological Psychiatry and Schizophrenia Bulletin.

In The Last Decade

David Popovic

14 papers receiving 233 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Popovic Germany 6 85 69 39 37 33 16 235
Jianbai Liu China 8 100 1.2× 77 1.1× 55 1.4× 37 1.0× 18 0.5× 16 420
Kristel Klaus United Kingdom 8 29 0.3× 30 0.4× 34 0.9× 48 1.3× 35 1.1× 13 321
Mario Gil United States 8 58 0.7× 38 0.6× 53 1.4× 31 0.8× 13 0.4× 17 349
Allonna Harker Canada 10 33 0.4× 47 0.7× 21 0.5× 37 1.0× 8 0.2× 13 370
Shi‐Kwang Lin Taiwan 7 100 1.2× 94 1.4× 70 1.8× 21 0.6× 3 0.1× 11 288
Ryoko Nakagawa Japan 9 45 0.5× 11 0.2× 26 0.7× 31 0.8× 35 1.1× 15 325
Laura Koenders Netherlands 8 112 1.3× 50 0.7× 100 2.6× 6 0.2× 22 0.7× 14 360
Amelia Cuarenta United States 6 21 0.2× 56 0.8× 52 1.3× 20 0.5× 4 0.1× 9 363
Mitsue Nagamine Japan 7 28 0.3× 76 1.1× 13 0.3× 10 0.3× 6 0.2× 19 299
Benjamin Ragen United States 12 18 0.2× 29 0.4× 77 2.0× 26 0.7× 21 0.6× 13 343

Countries citing papers authored by David Popovic

Since Specialization
Citations

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

Fields of papers citing papers by David Popovic

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Popovic

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

All Works

16 of 16 papers shown
1.
Popovic, David, Daniel Keeser, Kolja Schiltz, et al.. (2024). EEG-based Signatures of Schizophrenia, Depression, and Aberrant Aging: A Supervised Machine Learning Investigation. Schizophrenia Bulletin. 51(3). 804–817. 2 indexed citations
2.
Barton, Barbara B., David Popovic, Andrea Schmitt, et al.. (2024). Who is at risk for weight gain after weight‐gain associated treatment with antipsychotics, antidepressants, and mood stabilizers: A machine learning approach. Acta Psychiatrica Scandinavica. 151(3). 231–244. 2 indexed citations
3.
Popovic, David, Vladislav Yakimov, Sergi Papiol, et al.. (2024). Signature of Altered Retinal Microstructures and Electrophysiology in Schizophrenia Spectrum Disorders Is Associated With Disease Severity and Polygenic Risk. Biological Psychiatry. 96(10). 792–803. 8 indexed citations
4.
Popovic, David, Anne Ruef, Raimo K. R. Salokangas, et al.. (2024). Multivariate associations between psychiatric drug intake and grey matter volume changes in individuals at early stages of psychosis and depression. European Psychiatry. 67(S1). S272–S273. 1 indexed citations
5.
Popovic, David, Kolja Schiltz, Henrik Dobrowolny, et al.. (2023). Serum levels of neurofilament light-chain (NfL), a biomarker of axonal and synaptic damage, predict 5-year outcome in acutely ill schizophrenia patients. Journal of Affective Disorders Reports. 12. 100568–100568. 4 indexed citations
6.
Tiihonen, Jari, Juuso T. Korhonen, David Popovic, et al.. (2023). Effects of Substance Use and Antisocial Personality on Neuroimaging-Based Machine Learning Prediction of Schizophrenia. Schizophrenia Bulletin. 49(6). 1568–1578. 6 indexed citations
7.
Popovic, David, Joern Kaufmann, Markku Lähteenvuo, et al.. (2023). Patterns of risk—Using machine learning and structural neuroimaging to identify pedophilic offenders. Frontiers in Psychiatry. 14. 1001085–1001085. 4 indexed citations
8.
Guest, Paul C., David Popovic, & Jo hann Steiner. (2022). Challenges of Multiplex Assays for COVID-19 Research: A Machine Learning Perspective. Methods in molecular biology. 2511. 37–50.
9.
Giuliani, Luigi, David Popovic, Nikolaos Koutsouleris, et al.. (2021). Investigation of electrophysiological markers to predict clinical and functional outcome of schizophrenia using sparse partial least square regression. European Psychiatry. 64(S1). S542–S542.
10.
Raabe, Florian J., Elias Wagner, David Popovic, et al.. (2020). Classical blood biomarkers identify patients with higher risk for relapse 6 months after alcohol withdrawal treatment. European Archives of Psychiatry and Clinical Neuroscience. 271(5). 891–902. 4 indexed citations
11.
Popovic, David, Kolja Schiltz, Peter Falkai, & Nikolaos Koutsouleris. (2020). Präzisionspsychiatrie und der Beitrag von Brain Imaging und anderen Biomarkern. Fortschritte der Neurologie · Psychiatrie. 88(12). 778–785. 1 indexed citations
12.
Popovic, David, Andrea Schmitt, Lalit Kaurani, et al.. (2019). Childhood Trauma in Schizophrenia: Current Findings and Research Perspectives. Frontiers in Neuroscience. 13. 274–274. 115 indexed citations
13.
Papiol, Sergi, David Popovic, Daniel Keeser, et al.. (2017). Polygenic risk has an impact on the structural plasticity of hippocampal subfields during aerobic exercise combined with cognitive remediation in multi-episode schizophrenia. Translational Psychiatry. 7(6). e1159–e1159. 33 indexed citations
14.
Palm, Ulrich, et al.. (2017). P017 Transcranial direct current stimulation (tDCS) for the treatment of depression during pregnancy: A pilot study. Clinical Neurophysiology. 128(3). e17–e18. 7 indexed citations
15.
Bukumirić, Zoran, et al.. (2017). Problematic internet use among adolescents – gender differences. European Neuropsychopharmacology. 27. S1080–S1080. 1 indexed citations
16.
Trannoy, Séverine, et al.. (2016). Short and long-lasting behavioral consequences of agonistic encounters between male Drosophila melanogaster. Proceedings of the National Academy of Sciences. 113(17). 4818–4823. 47 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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2026