Matthias Hüser

1.6k total citations · 1 hit paper
9 papers, 258 citations indexed

About

Matthias Hüser is a scholar working on Artificial Intelligence, Epidemiology and Signal Processing. According to data from OpenAlex, Matthias Hüser has authored 9 papers receiving a total of 258 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Epidemiology and 3 papers in Signal Processing. Recurrent topics in Matthias Hüser's work include Machine Learning in Healthcare (5 papers), Sepsis Diagnosis and Treatment (3 papers) and Time Series Analysis and Forecasting (3 papers). Matthias Hüser is often cited by papers focused on Machine Learning in Healthcare (5 papers), Sepsis Diagnosis and Treatment (3 papers) and Time Series Analysis and Forecasting (3 papers). Matthias Hüser collaborates with scholars based in Switzerland, New Zealand and United States. Matthias Hüser's co-authors include Gunnar Rätsch, Martin Faltys, Xinrui Lyu, Marc Zimmermann, Stephanie L. Hyland, Bastian Rieck, Karsten Borgwardt, Thomas Gumbsch, Christian Bock and Max Horn and has published in prestigious journals such as Nature Medicine, Bioinformatics and Pharmacoepidemiology and Drug Safety.

In The Last Decade

Matthias Hüser

9 papers receiving 252 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Early prediction of circulatory failure in the intensive care unit using machine learning

2020 233 citations Stephanie L. Hyland, Martin Faltys et al. Nature Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthias Hüser Switzerland	4	121	92	48	45	38	9	258
Martin Faltys Switzerland	5	117 1.0×	93 1.0×	47 1.0×	45 1.0×	38 1.0×	8	258
Thomas Gumbsch Switzerland	4	127 1.0×	89 1.0×	48 1.0×	46 1.0×	36 0.9×	8	270
Stephanie L. Hyland United States	5	162 1.3×	87 0.9×	61 1.3×	56 1.2×	71 1.9×	10	338
Farah E. Shamout United Kingdom	8	107 0.9×	72 0.8×	27 0.6×	31 0.7×	21 0.6×	18	300
Simon Meyer Lauritsen Denmark	5	251 2.1×	132 1.4×	39 0.8×	37 0.8×	82 2.2×	7	418
Francesca Raimondi United Kingdom	7	140 1.2×	59 0.6×	99 2.1×	32 0.7×	43 1.1×	8	371
Rohit Joshi United States	7	206 1.7×	89 1.0×	20 0.4×	24 0.5×	18 0.5×	7	310
Mathias Vassard Olsen Denmark	5	155 1.3×	47 0.5×	36 0.8×	17 0.4×	64 1.7×	5	315
Hamid Mohamadlou United States	7	128 1.1×	123 1.3×	14 0.3×	32 0.7×	20 0.5×	10	248
Laura Moss United Kingdom	9	54 0.4×	111 1.2×	38 0.8×	46 1.0×	13 0.3×	40	382

Countries citing papers authored by Matthias Hüser

Since Specialization

Citations

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

Fields of papers citing papers by Matthias Hüser

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthias Hüser

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

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Stein, Ellen, Matthias Hüser, E. Susan Amirian, Matvey B. Palchuk, & Jeffrey S. Brown. (2025). TriNetX Dataworks‐ USA : Overview of a Multi‐Purpose, De‐Identified, Federated Electronic Health Record Real‐World Data and Analytics Network and Comparison to the US Census. Pharmacoepidemiology and Drug Safety. 34(9). e70198–e70198. 1 indexed citations

2.

Hüser, Matthias, Thomas Gumbsch, Martin Faltys, et al.. (2024). An empirical study on KDIGO-defined acute kidney injury prediction in the intensive care unit. Bioinformatics. 40(Supplement_1). i247–i256. 3 indexed citations

3.

Hüser, Matthias, et al.. (2021). T-DPSOM. 236–245. 5 indexed citations

4.

Zimmermann, Marc, et al.. (2021). HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data. arXiv (Cornell University). 6 indexed citations

5.

Hyland, Stephanie L., Martin Faltys, Matthias Hüser, et al.. (2020). Early prediction of circulatory failure in the intensive care unit using machine learning. Nature Medicine. 26(3). 364–373. 233 indexed citations breakdown →

6.

Hüser, Matthias, et al.. (2019). Variational pSOM: Deep Probabilistic Clustering with Self-Organizing Maps. 1 indexed citations

7.

Hüser, Matthias, et al.. (2018). Predicting circulatory system deterioration in intensive care unit patients.. International Joint Conference on Artificial Intelligence. 87–92. 2 indexed citations

8.

Fortuin, Vincent, Matthias Hüser, Francesco Locatello, Heiko Strathmann, & Gunnar Rätsch. (2018). Deep Self-Organization: Interpretable Discrete Representation Learning on Time Series. 6 indexed citations

9.

Hüser, Matthias, Valéria De Luca, Martin Jaggi, Walter Karlen, & E. Keller. (2015). Forecasting intracranial hypertension using waveform and time series features. 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.

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