David Schmidt

1.8k total citations · 1 hit paper
60 papers, 1.1k citations indexed

About

David Schmidt is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Signal Processing. According to data from OpenAlex, David Schmidt has authored 60 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 11 papers in Cognitive Neuroscience and 10 papers in Signal Processing. Recurrent topics in David Schmidt's work include Blind Source Separation Techniques (7 papers), Neural dynamics and brain function (6 papers) and Functional Brain Connectivity Studies (6 papers). David Schmidt is often cited by papers focused on Blind Source Separation Techniques (7 papers), Neural dynamics and brain function (6 papers) and Functional Brain Connectivity Studies (6 papers). David Schmidt collaborates with scholars based in United States, Germany and China. David Schmidt's co-authors include C. C. Wood, John George, John P. George, Wolfgang Utschick, Randall Berry, Changxin Shi, Michael L. Honig, Eric H. Westin, Michael F. Clarke and Flossie Wong‐Staal and has published in prestigious journals such as Nature, NeuroImage and ACM Computing Surveys.

In The Last Decade

David Schmidt

53 papers receiving 1.1k citations

Hit Papers

Screening performance and characteristics of breast cance... 2025 2026 2025 10 20 30

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Schmidt United States 17 298 203 188 181 144 60 1.1k
Francis M. Bui Canada 23 98 0.3× 135 0.7× 271 1.4× 194 1.1× 389 2.7× 131 2.0k
Md Saiful Islam Saudi Arabia 18 229 0.8× 159 0.8× 128 0.7× 38 0.2× 158 1.1× 72 1.0k
Vasileios Megalooikonomou Greece 25 219 0.7× 270 1.3× 299 1.6× 168 0.9× 531 3.7× 136 1.9k
Byunghan Lee South Korea 12 148 0.5× 114 0.6× 95 0.5× 86 0.5× 346 2.4× 22 1.6k
Michael B. Cohen United States 25 659 2.2× 52 0.3× 31 0.2× 133 0.7× 336 2.3× 70 1.9k
Edward Suh United States 18 49 0.2× 52 0.3× 87 0.5× 148 0.8× 299 2.1× 29 1.6k
Gilles Wainrib France 14 465 1.6× 99 0.5× 454 2.4× 55 0.3× 558 3.9× 35 1.7k
James Ford United States 24 128 0.4× 83 0.4× 260 1.4× 299 1.7× 477 3.3× 74 2.0k
Nagaaki Ohyama Japan 25 78 0.3× 82 0.4× 384 2.0× 54 0.3× 251 1.7× 215 2.9k
Cheng Li China 20 43 0.1× 135 0.7× 150 0.8× 28 0.2× 208 1.4× 81 1.7k

Countries citing papers authored by David Schmidt

Since Specialization
Citations

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

Fields of papers citing papers by David Schmidt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Schmidt

This figure shows the co-authorship network connecting the top 25 collaborators of David Schmidt. A scholar is included among the top collaborators of David Schmidt 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 Schmidt. David Schmidt 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.
Härtung, Matthias, et al.. (2025). Summarizing Online Patient Conversations Using Generative Language Models: Experimental and Comparative Study. JMIR Medical Informatics. 13. e62909–e62909.
2.
Bendahl, Pär‐Ola, Ida Arvidsson, Magnus Dustler, et al.. (2025). Deep learning on routine full-breast mammograms enhances lymph node metastasis prediction in early breast cancer. npj Digital Medicine. 8(1). 425–425.
3.
Sartor, Hanna, David Schmidt, Anna-Maria Larsson, et al.. (2025). Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, single-blinded, screening accuracy study. The Lancet Digital Health. 7(3). e175–e183. 35 indexed citations breakdown →
5.
Witte, Christian, David Schmidt, & Philipp Cimiano. (2024). Comparing generative and extractive approaches to information extraction from abstracts describing randomized clinical trials. Journal of Biomedical Semantics. 15(1). 3–3. 1 indexed citations
6.
Schmidt, David, et al.. (2020). SCSSnet: Learning Spatially-Conditioned Scene Segmentation on LiDAR Point Clouds.. 1086–1093. 2 indexed citations
7.
Yu, Mingxin, Yingzi Lin, David Schmidt, Xiangzhou Wang, & Yu Wang. (2014). Human-Robot Interaction Based on Gaze Gestures for the Drone Teleoperation. Journal of Eye Movement Research. 7(4). 33 indexed citations
8.
Wysham, Nicholas G., Richard A. Mularski, David Schmidt, et al.. (2013). Long-term persistence of quality improvements for an intensive care unit communication initiative using the VALUE strategy. Journal of Critical Care. 29(3). 450–454. 22 indexed citations
9.
Elkana, Odelia, Ram Frost, Uri Kramer, et al.. (2009). Cerebral reorganization as a function of linguistic recovery in children: An fMRI study. Cortex. 47(2). 202–216. 26 indexed citations
10.
Jun, Sung Chan, John George, Woohan Kim, et al.. (2008). Bayesian brain source imaging based on combined MEG/EEG and fMRI using MCMC. NeuroImage. 40(4). 1581–1594. 14 indexed citations
11.
Plis, Sergey, et al.. (2007). Modeling spatiotemporal covariance for magnetoencephalography or electroencephalography source analysis. Physical Review E. 75(1). 11928–11928. 5 indexed citations
12.
Jun, Sung Chan, John George, Sergey Plis, et al.. (2006). Improving source detection and separation in a spatiotemporal Bayesian inference dipole analysis. Physics in Medicine and Biology. 51(10). 2395–2414. 16 indexed citations
13.
Jun, Sung Chan, Sergey Plis, Doug Ranken, & David Schmidt. (2006). Spatiotemporal noise covariance estimation from limited empirical magnetoencephalographic data. Physics in Medicine and Biology. 51(21). 5549–5564. 7 indexed citations
14.
Guernic, Gurvan Le, Anindya Banerjee, & David Schmidt. (2006). Automaton-based Non-interference Monitoring. HAL (Le Centre pour la Communication Scientifique Directe). 49.
15.
Schmidt, David. (2000). Continuous probability distributions from finite data. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 61(2). 1052–1055. 5 indexed citations
16.
Schmidt, David, John P. George, & C. C. Wood. (1999). Bayesian inference applied to the electromagnetic inverse problem. Human Brain Mapping. 7(3). 195–212. 102 indexed citations
17.
Moubayed, Pierre, et al.. (1995). Carcinoma of the uterine cervix associated with schistosomiasis and induced by human papillomaviruses. International Journal of Gynecology & Obstetrics. 49(2). 175–179. 30 indexed citations
18.
George, John, Cheryl J. Aine, John C. Mosher, et al.. (1995). Mapping Function in the Human Brain with Magnetoencephalography, Anatomical Magnetic Resonance Imaging, and Functional Magnetic Resonance Imaging. Journal of Clinical Neurophysiology. 12(5). 406–431. 156 indexed citations
19.
Mizuno, Masaaki & David Schmidt. (1992). A security flow control algorithm and its denotational semantics correctness proof. Formal Aspects of Computing. 4(Suppl 1). 727–754. 36 indexed citations
20.
Schmidt, David & Michael A. McClinton. (1990). Microvascular anastomoses in replanted fingers: Do they stay open?. Microsurgery. 11(3). 251–254. 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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