Christopher Martin Sauer

418 total citations
16 papers, 218 citations indexed

About

Christopher Martin Sauer is a scholar working on Artificial Intelligence, Economics and Econometrics and General Health Professions. According to data from OpenAlex, Christopher Martin Sauer has authored 16 papers receiving a total of 218 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 4 papers in Economics and Econometrics and 3 papers in General Health Professions. Recurrent topics in Christopher Martin Sauer's work include Machine Learning in Healthcare (3 papers), Health Systems, Economic Evaluations, Quality of Life (3 papers) and Sepsis Diagnosis and Treatment (3 papers). Christopher Martin Sauer is often cited by papers focused on Machine Learning in Healthcare (3 papers), Health Systems, Economic Evaluations, Quality of Life (3 papers) and Sepsis Diagnosis and Treatment (3 papers). Christopher Martin Sauer collaborates with scholars based in United States, Germany and Netherlands. Christopher Martin Sauer's co-authors include Leo Anthony Celi, Paul Elbers, Armand R. J. Girbes, Li-Ching Chen, Daniele Ramazzotti, Jinghui Dong, Iván Sánchez Fernández, Kenneth Paik, Ben Illigens and Daniel T. Myran and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of Medical Internet Research.

In The Last Decade

Christopher Martin Sauer

11 papers receiving 209 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christopher Martin Sauer United States 7 60 53 36 32 30 16 218
Xuan Song China 8 54 0.9× 47 0.9× 53 1.5× 41 1.3× 25 0.8× 30 376
Maren E. Shipe United States 5 53 0.9× 61 1.2× 54 1.5× 71 2.2× 28 0.9× 16 334
Anna Siefkas United States 9 72 1.2× 81 1.5× 94 2.6× 38 1.2× 36 1.2× 17 325
Alexander Pate United Kingdom 9 51 0.8× 43 0.8× 13 0.4× 24 0.8× 20 0.7× 24 247
Miguel Ángel Armengol de la Hoz Spain 11 65 1.1× 44 0.8× 26 0.7× 27 0.8× 23 0.8× 24 287
Hoyt Burdick United States 7 76 1.3× 102 1.9× 89 2.5× 24 0.8× 33 1.1× 8 269
Nianzong Hou China 5 143 2.4× 101 1.9× 52 1.4× 47 1.5× 28 0.9× 9 369
Andrew P. Michelson United States 11 140 2.3× 68 1.3× 27 0.8× 55 1.7× 12 0.4× 32 467
Chris Knoll United States 4 30 0.5× 41 0.8× 15 0.4× 12 0.4× 33 1.1× 4 260
Siddharth Gosavi India 8 33 0.6× 40 0.8× 55 1.5× 30 0.9× 20 0.7× 24 297

Countries citing papers authored by Christopher Martin Sauer

Since Specialization
Citations

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

Fields of papers citing papers by Christopher Martin Sauer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher Martin Sauer. 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 Christopher Martin Sauer. The network helps show where Christopher Martin Sauer may publish in the future.

Co-authorship network of co-authors of Christopher Martin Sauer

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher Martin Sauer. A scholar is included among the top collaborators of Christopher Martin Sauer 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 Christopher Martin Sauer. Christopher Martin Sauer 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.
Alberto, Nicole Rose I., et al.. (2025). Technological Solutions to Improve Inpatient Handover in the Era of Artificial Intelligence: Scoping Review. Journal of Medical Internet Research. 27. e70358–e70358.
2.
Struja, Tristan, Christopher Martin Sauer, Martine Otten, et al.. (2025). Sharing is caring: A systematic review of publicly available intensive care data sets. Journal of Critical Care. 90. 155205–155205.
3.
Sauer, Christopher Martin, et al.. (2025). The Data Artifacts Glossary: a community-based repository for bias on health datasets. Journal of Biomedical Science. 32(1). 14–14. 1 indexed citations
4.
Struja, Tristan, Barbara D. Lam, Xiaoli Liu, et al.. (2025). Evaluating equitable care in the ICU:Creating a causal inference template to assess the impact of life-sustaining interventions across racial and ethnic groups. Heart & Lung. 72. 48–56. 1 indexed citations
5.
6.
Markussen, Dagfinn Lunde, et al.. (2024). Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study. Journal of Medical Internet Research. 26. e56382–e56382. 1 indexed citations
7.
8.
Thoral, Patrick, et al.. (2024). Development and clinical implementation of real-time decision support tools for ICU discharge. Journal of Critical Care. 81. 154558–154558.
9.
Sauer, Christopher Martin, Tom Hendriks, Femke Ongenae, et al.. (2023). Generalizable calibrated machine learning models for real-time atrial fibrillation risk prediction in ICU patients. International Journal of Medical Informatics. 175. 105086–105086. 14 indexed citations
10.
Sauer, Christopher Martin, et al.. (2022). Leveraging electronic health records for data science: common pitfalls and how to avoid them. The Lancet Digital Health. 4(12). e893–e898. 70 indexed citations
11.
Sauer, Christopher Martin, Josep Gómez, David R. Ziehr, et al.. (2021). Understanding critically ill sepsis patients with normal serum lactate levels: results from U.S. and European ICU cohorts. Scientific Reports. 11(1). 20076–20076. 22 indexed citations
12.
Donado, Carolina, Patrik Bächtiger, Christopher Martin Sauer, et al.. (2019). Machine learning can accurately predict pre-admission baseline hemoglobin and creatinine in intensive care patients. npj Digital Medicine. 2(1). 116–116. 18 indexed citations
13.
Sauer, Christopher Martin, et al.. (2018). Effect of long term aspirin use on the incidence of prostate cancer: A systematic review and meta-analysis. Critical Reviews in Oncology/Hematology. 132. 66–75. 24 indexed citations
14.
Sauer, Christopher Martin, et al.. (2018). Feature selection and prediction of treatment failure in tuberculosis. PLoS ONE. 13(11). e0207491–e0207491. 37 indexed citations
15.
Sauer, Christopher Martin, Jinghui Dong, Leo Anthony Celi, & Daniele Ramazzotti. (2018). Improved Survival of Cancer Patients Admitted to the Intensive Care Unit between 2002 and 2011 at a U.S. Teaching Hospital. Cancer Research and Treatment. 51(3). 973–981. 25 indexed citations
16.
Sauer, Christopher Martin, et al.. (2017). Merkelzellkarzinom: kutane Manifestation einer hochmalignen Prä-/pro-B-Zell-Neoplasie?. Der Hautarzt. 68(3). 204–210. 5 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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