Patrick Schwab

1.5k total citations
64 papers, 754 citations indexed

About

Patrick Schwab is a scholar working on Condensed Matter Physics, Artificial Intelligence and Materials Chemistry. According to data from OpenAlex, Patrick Schwab has authored 64 papers receiving a total of 754 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Condensed Matter Physics, 13 papers in Artificial Intelligence and 11 papers in Materials Chemistry. Recurrent topics in Patrick Schwab's work include Physics of Superconductivity and Magnetism (13 papers), Magnetic properties of thin films (9 papers) and Machine Learning in Healthcare (7 papers). Patrick Schwab is often cited by papers focused on Physics of Superconductivity and Magnetism (13 papers), Magnetic properties of thin films (9 papers) and Machine Learning in Healthcare (7 papers). Patrick Schwab collaborates with scholars based in Switzerland, Austria and Germany. Patrick Schwab's co-authors include D. Bäuerle, Walter Karlen, Stefan Bauer, W. Lang, Jürgen Hetzel, Uli Lemmer, Hans‐Jürgen Eisler, Leo Anthony Celi, Sergios Gatidis and J. Heitz and has published in prestigious journals such as Nature Medicine, SHILAP Revista de lepidopterología and Nano Letters.

In The Last Decade

Patrick Schwab

58 papers receiving 728 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Patrick Schwab 198 148 131 129 116 64 754
Aonghus Lawlor 155 0.8× 360 2.4× 194 1.5× 22 0.2× 45 0.4× 79 1.1k
Nicolas Laurent 131 0.7× 64 0.4× 151 1.2× 66 0.5× 243 2.1× 62 820
Ali Behrooz 140 0.7× 36 0.2× 100 0.8× 28 0.2× 115 1.0× 25 391
P. R. Eastham 126 0.6× 387 2.6× 365 2.8× 52 0.4× 1.4k 11.8× 65 1.9k
Jeff Gibbs 30 0.2× 206 1.4× 149 1.1× 16 0.1× 70 0.6× 2 828
Richard L. J. Qiu 55 0.3× 57 0.4× 169 1.3× 32 0.2× 211 1.8× 58 786
Matthias Grimm 60 0.3× 24 0.2× 291 2.2× 20 0.2× 175 1.5× 39 817
Yuguang Chen 67 0.3× 338 2.3× 98 0.7× 51 0.4× 290 2.5× 126 1.4k
Daiju Ueda 360 1.8× 378 2.6× 287 2.2× 101 0.8× 224 1.9× 123 2.3k
Alexander Thieme 23 0.1× 61 0.4× 183 1.4× 25 0.2× 68 0.6× 23 496

Countries citing papers authored by Patrick Schwab

Since Specialization
Citations

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

Fields of papers citing papers by Patrick Schwab

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Patrick Schwab

This figure shows the co-authorship network connecting the top 25 collaborators of Patrick Schwab. A scholar is included among the top collaborators of Patrick Schwab 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 Patrick Schwab. Patrick Schwab 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.
Liu, Fenglin, Li Zheng, Qingyu Yin, et al.. (2025). A multimodal multidomain multilingual medical foundation model for zero shot clinical diagnosis. npj Digital Medicine. 8(1). 86–86. 5 indexed citations
2.
Chauhan, Vinod Kumar, Lei Clifton, Huiqi Lu, et al.. (2025). Sample Selection Bias in Machine Learning for Healthcare. 6(4). 1–24. 1 indexed citations
3.
Roohani, Yusuf, et al.. (2025). A large-scale benchmark for network inference from single-cell perturbation data. Communications Biology. 8(1). 412–412. 3 indexed citations
4.
Littmann, Maria, Max Horn, Andreas Georgiou, et al.. (2025). Varicella-zoster virus reactivation and the risk of dementia. Nature Medicine. 31(12). 4172–4179. 3 indexed citations
5.
Georgiou, Andreas, et al.. (2025). In silico biological discovery with large perturbation models. Nature Computational Science. 5(11). 1029–1040. 1 indexed citations
6.
Schwab, Patrick, Maria Littmann, Carolyn Buser‐Doepner, et al.. (2024). Recombinant zoster vaccine and reduced risk of dementia: matched‐cohort study using large‐scale electronic health records and machine learning methodology. Alzheimer s & Dementia. 20(S7). 2 indexed citations
7.
Molaei, Soheila, Fenglin Liu, Andrew A. S. Soltan, et al.. (2024). Knowledge abstraction and filtering based federated learning over heterogeneous data views in healthcare. npj Digital Medicine. 7(1). 283–283. 3 indexed citations
8.
Shields, Ryan K., Wendy Y. Cheng, Ashish V. Joshi, et al.. (2024). Development of Predictive Models to Inform a Novel Risk Categorization Framework for Antibiotic Resistance in Escherichia coli–Caused Uncomplicated Urinary Tract Infection. Clinical Infectious Diseases. 79(2). 295–304.
9.
Kabiljo, Renata, Ahmad Al Khleifat, Ashley Jones, et al.. (2023). Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data. Acta Neuropathologica Communications. 11(1). 208–208. 15 indexed citations
10.
Spörri, Jörg, et al.. (2023). Addressing the unresolved challenge of quantifying skiing exposure—A proof of concept using smartphone sensors. Frontiers in Sports and Active Living. 5. 1157987–1157987. 1 indexed citations
11.
Shields, Ryan K., Wendy Y. Cheng, Ashish V. Joshi, et al.. (2023). 2838. Clinical Application and Validation of a Predictive Antimicrobial Resistance Risk Categorization Framework for Patients with Uncomplicated Urinary Tract Infection. Open Forum Infectious Diseases. 10(Supplement_2). 1 indexed citations
12.
Bauer, Stefan, et al.. (2022). Conditional generation of medical time series for extrapolation to underrepresented populations. SHILAP Revista de lepidopterología. 1(7). e0000074–e0000074. 9 indexed citations
13.
Seastedt, Kenneth P., Patrick Schwab, Edith K. Wakida, et al.. (2022). Global healthcare fairness: We should be sharing more, not less, data. SHILAP Revista de lepidopterología. 1(10). e0000102–e0000102. 48 indexed citations
14.
Machann, Jürgen, Martin Heni, Patrick Schwab, et al.. (2021). Detection of diabetes from whole-body MRI using deep learning. JCI Insight. 6(21). 13 indexed citations
15.
Schwab, Patrick, et al.. (2020). Clinical Predictive Models for COVID-19: Systematic Study. Journal of Medical Internet Research. 22(10). e21439–e21439. 68 indexed citations
16.
Muroi, Carl, Valéria De Luca, D. Mack, et al.. (2019). Automated False Alarm Reduction in a Real-Life Intensive Care Setting Using Motion Detection. Neurocritical Care. 32(2). 419–426. 17 indexed citations
17.
Schwab, Patrick & Helmut Hlavacs. (2015). Capturing the Essence: Towards the Automated Generation of Transparent Behavior Models. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 11(1). 184–190. 6 indexed citations
18.
Liu, Xin, Sergei Lebedkin, Heino Besser, et al.. (2014). Tailored Surface-Enhanced Raman Nanopillar Arrays Fabricated by Laser-Assisted Replication for Biomolecular Detection Using Organic Semiconductor Lasers. ACS Nano. 9(1). 260–270. 40 indexed citations
19.
Schwab, Patrick, et al.. (2003). A NEW RUSSIAN WASTE MANAGEMENT INSTALLATION. University of North Texas Digital Library (University of North Texas). 1 indexed citations
20.
Schwab, Patrick, et al.. (2002). Russian Containers for Transportation of Solid Radioactive Waste. University of North Texas Digital Library (University of North Texas). 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Aonghus Lawlor Breakdown of academic impact, for papers by Nicolas Laurent Breakdown of academic impact, for papers by Ali Behrooz Breakdown of academic impact, for papers by P. R. Eastham Breakdown of academic impact, for papers by Jeff Gibbs Breakdown of academic impact, for papers by Richard L. J. Qiu Breakdown of academic impact, for papers by Matthias Grimm Breakdown of academic impact, for papers by Yuguang Chen Breakdown of academic impact, for papers by Daiju Ueda Breakdown of academic impact, for papers by Alexander Thieme
Rankless by CCL
2026