Samson Mataraso

1.6k total citations
22 papers, 559 citations indexed

About

Samson Mataraso is a scholar working on Epidemiology, Artificial Intelligence and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Samson Mataraso has authored 22 papers receiving a total of 559 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Epidemiology, 7 papers in Artificial Intelligence and 6 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Samson Mataraso's work include Machine Learning in Healthcare (7 papers), Sepsis Diagnosis and Treatment (5 papers) and COVID-19 diagnosis using AI (3 papers). Samson Mataraso is often cited by papers focused on Machine Learning in Healthcare (7 papers), Sepsis Diagnosis and Treatment (5 papers) and COVID-19 diagnosis using AI (3 papers). Samson Mataraso collaborates with scholars based in United States and Belgium. Samson Mataraso's co-authors include Ritankar Das, David Shimabukuro, Christopher W. Barton, Mitchell D. Feldman, Jana Hoffman, Abigail Green‐Saxena, Jacob Calvert, Emily Pellegrini, Gina Barnes and Andrea J. McCoy and has published in prestigious journals such as Circulation, Nature Communications and Brain.

In The Last Decade

Samson Mataraso

18 papers receiving 529 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Samson Mataraso United States 10 219 218 149 109 83 22 559
Emily Pellegrini United States 13 207 0.9× 243 1.1× 164 1.1× 88 0.8× 68 0.8× 25 611
Lucas M. Fleuren Netherlands 11 217 1.0× 345 1.6× 81 0.5× 91 0.8× 40 0.5× 22 708
Sayon Dutta United States 10 111 0.5× 142 0.7× 121 0.8× 73 0.7× 39 0.5× 42 552
Erkin Ötleş United States 10 242 1.1× 225 1.0× 137 0.9× 289 2.7× 78 0.9× 19 770
Luca F. Roggeveen Netherlands 9 192 0.9× 309 1.4× 66 0.4× 72 0.7× 36 0.4× 14 612
Tingjie Guo Netherlands 11 190 0.9× 329 1.5× 67 0.4× 66 0.6× 34 0.4× 24 682
Michiel Schinkel Netherlands 13 187 0.9× 216 1.0× 198 1.3× 365 3.3× 67 0.8× 31 800
Gina Barnes United States 13 129 0.6× 104 0.5× 109 0.7× 78 0.7× 51 0.6× 31 486
Gabriel Wardi United States 17 184 0.8× 370 1.7× 57 0.4× 81 0.7× 34 0.4× 75 779
Joseph R. Pare United States 11 151 0.7× 201 0.9× 143 1.0× 36 0.3× 61 0.7× 26 668

Countries citing papers authored by Samson Mataraso

Since Specialization
Citations

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

Fields of papers citing papers by Samson Mataraso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Samson Mataraso

This figure shows the co-authorship network connecting the top 25 collaborators of Samson Mataraso. A scholar is included among the top collaborators of Samson Mataraso 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 Samson Mataraso. Samson Mataraso 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.
Mataraso, Samson, et al.. (2025). Benchmarking of pre-training strategies for electronic health record foundation models. JAMIA Open. 8(4). ooaf090–ooaf090.
2.
Bukhari, Syed, Lei Xue, David Seong, et al.. (2025). Deep learning-based cell type profiles reveal signatures of Alzheimer’s disease resilience and resistance. Brain. 148(10). 3665–3678.
3.
Mataraso, Samson, Camilo Espinosa, David Seong, et al.. (2025). A machine learning approach to leveraging electronic health records for enhanced omics analysis. Nature Machine Intelligence. 7(2). 293–306. 13 indexed citations
4.
Reiss, Jonathan D., Samson Mataraso, Ivana Marić, et al.. (2025). Applications of Metabolomics and Lipidomics in the Neonatal Intensive Care Unit. NeoReviews. 26(2). e100–e114.
5.
Seong, David, Samson Mataraso, Camilo Espinosa, et al.. (2024). Generating pregnant patient biological profiles by deconvoluting clinical records with electronic health record foundation models. Briefings in Bioinformatics. 25(6). 2 indexed citations
6.
Phongpreecha, Thanaphong, Fiorella C. Grandi, Lei Xue, et al.. (2023). Whole genome deconvolution unveils Alzheimer’s resilient epigenetic signature. Nature Communications. 14(1). 4947–4947. 13 indexed citations
7.
Phongpreecha, Thanaphong, Camilo Espinosa, Brenna Cholerton, et al.. (2023). Quantitative estimate of cognitive resilience and its medical and genetic associations. Alzheimer s Research & Therapy. 15(1). 192–192. 4 indexed citations
8.
Mataraso, Samson, Gina Barnes, Sepideh Shokouhi, et al.. (2022). Enriching the Study Population for Ischemic Stroke Therapeutic Trials Using a Machine Learning Algorithm. Frontiers in Neurology. 12. 784250–784250. 3 indexed citations
9.
Mataraso, Samson, et al.. (2022). A machine learning approach to identifying patients with pulmonary hypertension using real-world electronic health records. International Journal of Cardiology. 374. 95–99. 22 indexed citations
10.
Mataraso, Samson, Gina Barnes, Jana Hoffman, et al.. (2021). Predicting pulmonary embolism among hospitalized patients with machine learning algorithms. Pulmonary Circulation. 12(1). e12013–e12013. 22 indexed citations
11.
Mataraso, Samson, Anna Siefkas, Emily Pellegrini, et al.. (2021). A Machine Learning Approach to Predict Deep Venous Thrombosis Among Hospitalized Patients. Clinical and Applied Thrombosis/Hemostasis. 27. 2875389713–2875389713. 31 indexed citations
12.
Allen, Angier, Samson Mataraso, Anna Siefkas, et al.. (2020). A Racially Unbiased, Machine Learning Approach to Prediction of Mortality: Algorithm Development Study. JMIR Public Health and Surveillance. 6(4). e22400–e22400. 35 indexed citations
13.
Burdick, Hoyt, Carson Lam, Samson Mataraso, et al.. (2020). Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial. Computers in Biology and Medicine. 124. 103949–103949. 96 indexed citations
14.
Lam, Carson, Samson Mataraso, Angier Allen, et al.. (2020). Mortality prediction model for the triage of COVID-19, pneumonia, and mechanically ventilated ICU patients: A retrospective study. Annals of Medicine and Surgery. 59. 207–216. 48 indexed citations
15.
Burdick, Hoyt, Carson Lam, Samson Mataraso, et al.. (2020). Is Machine Learning a Better Way to Identify COVID-19 Patients Who Might Benefit from Hydroxychloroquine Treatment?—The IDENTIFY Trial. Journal of Clinical Medicine. 9(12). 3834–3834. 6 indexed citations
16.
Mataraso, Samson, Emily Pellegrini, Gina Barnes, et al.. (2020). 371: A Machine Learning Approach to Predict Deep Venous Thrombosis Among Hospitalized Patients. Critical Care Medicine. 49(1). 175–175. 4 indexed citations
17.
Mataraso, Samson, Emily Pellegrini, Gina Barnes, et al.. (2020). Abstract 16723: A Machine Learning Approach to Acute Heart Failure Risk Stratification. Circulation. 142(Suppl_3). 1 indexed citations
18.
Lam, Carson, Samson Mataraso, Emily Pellegrini, et al.. (2020). Mortality Prediction Model for COVID-19, Pneumonia, and Mechanically Ventilated ICU Patients: A Retrospective Study. SSRN Electronic Journal.
19.
Le, Sidney, Samson Mataraso, Jacob Calvert, et al.. (2019). 24: EFFECTS OF MONOCYTE DISTRIBUTION WIDTH AND WHITE BLOOD CELL COUNT ON A SEPSIS PREDICTION ALGORITHM. Critical Care Medicine. 48(1). 12–12. 1 indexed citations
20.
Calvert, Jacob, Jana Hoffman, Christopher Barton, et al.. (2017). Cost and mortality impact of an algorithm-driven sepsis prediction system. Journal of Medical Economics. 20(6). 646–651. 20 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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