Alejandro Schuler

1.5k total citations
31 papers, 736 citations indexed

About

Alejandro Schuler is a scholar working on Artificial Intelligence, Epidemiology and Emergency Medicine. According to data from OpenAlex, Alejandro Schuler has authored 31 papers receiving a total of 736 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 8 papers in Epidemiology and 7 papers in Emergency Medicine. Recurrent topics in Alejandro Schuler's work include Neural Networks and Applications (7 papers), Machine Learning in Healthcare (6 papers) and Emergency and Acute Care Studies (6 papers). Alejandro Schuler is often cited by papers focused on Neural Networks and Applications (7 papers), Machine Learning in Healthcare (6 papers) and Emergency and Acute Care Studies (6 papers). Alejandro Schuler collaborates with scholars based in United States, Germany and United Kingdom. Alejandro Schuler's co-authors include Gabriel J. Escobar, Nigam H. Shah, Jean‐Louis Vincent, Patricia Kipnis, J Greene, Brian L. Lawson, Vincent X. Liu, Josef A. Nossek, Alison Callahan and Yun Lu and has published in prestigious journals such as New England Journal of Medicine, SHILAP Revista de lepidopterología and BMJ.

In The Last Decade

Alejandro Schuler

27 papers receiving 717 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alejandro Schuler United States 14 196 157 97 84 75 31 736
Chris Kelman Australia 15 192 1.0× 110 0.7× 73 0.8× 43 0.5× 129 1.7× 23 961
Petar Momčilović United States 15 68 0.3× 82 0.5× 235 2.4× 95 1.1× 56 0.7× 49 1.0k
Guilan Kong China 20 183 0.9× 360 2.3× 80 0.8× 54 0.6× 43 0.6× 57 1.1k
Oğuz Akbilgiç United States 22 138 0.7× 202 1.3× 373 3.8× 35 0.4× 34 0.5× 81 1.3k
Dukyong Yoon South Korea 22 116 0.6× 131 0.8× 310 3.2× 35 0.4× 42 0.6× 99 1.4k
David M. Maslove Canada 24 389 2.0× 226 1.4× 273 2.8× 161 1.9× 109 1.5× 73 1.9k
Shiying Hao United States 15 194 1.0× 167 1.1× 137 1.4× 102 1.2× 45 0.6× 43 774
Kevin Peterson United States 26 391 2.0× 53 0.3× 251 2.6× 50 0.6× 103 1.4× 106 2.0k
Jeremy Petch Canada 10 110 0.6× 150 1.0× 71 0.7× 30 0.4× 63 0.8× 27 717
Fatemeh Rahimian Sweden 9 102 0.5× 175 1.1× 112 1.2× 27 0.3× 27 0.4× 20 577

Countries citing papers authored by Alejandro Schuler

Since Specialization
Citations

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

Fields of papers citing papers by Alejandro Schuler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alejandro Schuler

This figure shows the co-authorship network connecting the top 25 collaborators of Alejandro Schuler. A scholar is included among the top collaborators of Alejandro Schuler 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 Alejandro Schuler. Alejandro Schuler 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.
Hubbard, Alan, et al.. (2025). Prognostic adjustment with efficient estimators to unbiasedly leverage historical data in randomized trials. The International Journal of Biostatistics. 21(1). 1–15. 2 indexed citations
2.
Sykulski, Adam M., et al.. (2023). Probabilistic Prediction of Oceanographic Velocities with Multivariate Gaussian Natural Gradient Boosting. SHILAP Revista de lepidopterología. 2. 2 indexed citations
3.
Schuler, Alejandro, et al.. (2023). SuperNOVA: Semi-Parametric Identification andEstimation of Interaction and Effect Modification in Mixed Exposuresusing Stochastic Interventions in R. The Journal of Open Source Software. 8(91). 5422–5422. 3 indexed citations
4.
5.
Flores, Alyssa M., Alejandro Schuler, Jeffrey W. Olin, et al.. (2021). Unsupervised Learning for Automated Detection of Coronary Artery Disease Subgroups. Journal of the American Heart Association. 10(23). e021976–e021976. 33 indexed citations
6.
Schuler, Alejandro, et al.. (2021). Increasing the efficiency of randomized trial estimates via linear adjustment for a prognostic score. The International Journal of Biostatistics. 18(2). 329–356. 16 indexed citations
7.
8.
Duan, Tony, Anand Avati, Daisy Yi Ding, et al.. (2020). NGBoost: Natural Gradient Boosting for Probabilistic Prediction. International Conference on Machine Learning. 1. 2690–2700. 69 indexed citations
9.
Escobar, Gabriel J., et al.. (2020). Prediction of obstetrical and fetal complications using automated electronic health record data. American Journal of Obstetrics and Gynecology. 224(2). 137–147.e7. 29 indexed citations
10.
Schuler, Alejandro, Alison Callahan, Kenneth Jung, & Nigam H. Shah. (2018). Performing an Informatics Consult: Methods and Challenges. Journal of the American College of Radiology. 15(3). 563–568. 21 indexed citations
11.
Wang, Jason K., Jason Hom, Alejandro Schuler, et al.. (2018). An evaluation of clinical order patterns machine-learned from clinician cohorts stratified by patient mortality outcomes. Journal of Biomedical Informatics. 86. 109–119. 11 indexed citations
12.
Schuler, Alejandro, Yun Lu, Theodore J. Iwashyna, et al.. (2018). The Impact of Acute Organ Dysfunction on Long-Term Survival in Sepsis*. Critical Care Medicine. 46(6). 843–849. 112 indexed citations
13.
Wang, Jason K., Alejandro Schuler, Nigam H. Shah, Michael Baiocchi, & Jonathan H. Chen. (2018). Inpatient Clinical Order Patterns Machine-Learned From Teaching Versus Attending-Only Medical Services.. PubMed. 2017. 226–235. 2 indexed citations
14.
Richman, Ilana B., Michael Fairley, Mads Emil Jørgensen, et al.. (2016). Cost-effectiveness of Intensive Blood Pressure Management. JAMA Cardiology. 1(8). 872–872. 46 indexed citations
15.
Schuler, Alejandro, Jean‐Louis Vincent, Joe Wan, et al.. (2015). DISCOVERING PATIENT PHENOTYPES USING GENERALIZED LOW RANK MODELS. PubMed. 21. 144–155. 19 indexed citations
16.
Schuler, Alejandro, et al.. (2003). Robustness of attractor networks and an improved convex corner detector. 55–61. 1 indexed citations
17.
Schuler, Alejandro, et al.. (2002). Hardware-oriented learning for cellular neural networks. 183–188. 3 indexed citations
18.
19.
Utschick, Wolfgang, et al.. (2002). The evaluation of feature extraction criteria applied to neural network classifiers. 1. 315–318. 4 indexed citations
20.
Schuler, Alejandro, et al.. (1993). Design of robust cellular neural networks. IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications. 40(5). 358–364. 54 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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