Thomas Desautels

1.1k total citations · 1 hit paper
10 papers, 633 citations indexed

About

Thomas Desautels is a scholar working on Artificial Intelligence, Epidemiology and Surgery. According to data from OpenAlex, Thomas Desautels has authored 10 papers receiving a total of 633 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Epidemiology and 2 papers in Surgery. Recurrent topics in Thomas Desautels's work include Sepsis Diagnosis and Treatment (5 papers), Machine Learning in Healthcare (4 papers) and Protein purification and stability (1 paper). Thomas Desautels is often cited by papers focused on Sepsis Diagnosis and Treatment (5 papers), Machine Learning in Healthcare (4 papers) and Protein purification and stability (1 paper). Thomas Desautels collaborates with scholars based in United States, United Kingdom and Switzerland. Thomas Desautels's co-authors include Ritankar Das, Jacob Calvert, Melissa Jay, Uli K. Chettipally, Jana Hoffman, David J. Wales, Yaniv Kerem, Chris W. Barton, Mitchell D. Feldman and Lisa Shieh and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Biomedical Engineering and Journal of Machine Learning Research.

In The Last Decade

Thomas Desautels

10 papers receiving 611 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.

Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach

2016 339 citations Thomas Desautels, Jacob Calvert et al. JMIR Medical Informatics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Thomas Desautels United States	9	388	348	91	82	68	10	633
Fereshteh Razmi United States	2	275 0.7×	309 0.9×	52 0.6×	88 1.1×	78 1.1×	2	516
Matthew D. Stanley United States	6	352 0.9×	381 1.1×	65 0.7×	131 1.6×	85 1.3×	8	681
Katharine E. Henry United States	8	448 1.2×	354 1.0×	92 1.0×	99 1.2×	189 2.8×	14	826
Lucas M. Fleuren Netherlands	11	217 0.6×	345 1.0×	40 0.4×	78 1.0×	91 1.3×	22	708
Chris W. Barton United States	3	233 0.6×	239 0.7×	55 0.6×	53 0.6×	45 0.7×	5	392
Melissa Jay United States	8	597 1.5×	625 1.8×	123 1.4×	136 1.7×	101 1.5×	11	925
Luca F. Roggeveen Netherlands	9	192 0.5×	309 0.9×	36 0.4×	74 0.9×	72 1.1×	14	612
Samson Mataraso United States	10	219 0.6×	218 0.6×	83 0.9×	52 0.6×	109 1.6×	22	559
Max Horn Switzerland	9	211 0.5×	207 0.6×	43 0.5×	60 0.7×	63 0.9×	17	507
Emily Pellegrini United States	13	207 0.5×	243 0.7×	68 0.7×	60 0.7×	88 1.3×	25	611

Countries citing papers authored by Thomas Desautels

Since Specialization

Citations

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

Fields of papers citing papers by Thomas Desautels

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Desautels

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

All Works

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10 of 10 papers shown

1.

Silva, Felipe Leno da, André Gonçalves, Ruben Glatt, et al.. (2023). Language model-accelerated deep symbolic optimization. Neural Computing and Applications. 37(31). 25601–25617. 1 indexed citations

2.

Zhu, Fangqiang, William F. Bennett, Edmond Y. Lau, et al.. (2022). Large-scale application of free energy perturbation calculations for antibody design. Scientific Reports. 12(1). 12489–12489. 14 indexed citations

3.

Desautels, Thomas, Ritankar Das, Jacob Calvert, et al.. (2017). Prediction of early unplanned intensive care unit readmission in a UK tertiary care hospital: a cross-sectional machine learning approach. BMJ Open. 7(9). e017199–e017199. 83 indexed citations

4.

Desautels, Thomas, Jacob Calvert, Jana Hoffman, et al.. (2017). Using Transfer Learning for Improved Mortality Prediction in a Data-Scarce Hospital Setting. PubMed. 9. 2718907427–2718907427. 40 indexed citations

5.

Desautels, Thomas, Jacob Calvert, Jana Hoffman, et al.. (2016). Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach. JMIR Medical Informatics. 4(3). e28–e28. 339 indexed citations breakdown →

6.

Calvert, Jacob, Qingqing Mao, Angela J. Rogers, et al.. (2016). A computational approach to mortality prediction of alcohol use disorder inpatients. Computers in Biology and Medicine. 75. 74–79. 15 indexed citations

7.

Calvert, Jacob, Thomas Desautels, Uli K. Chettipally, et al.. (2016). High-performance detection and early prediction of septic shock for alcohol-use disorder patients. Annals of Medicine and Surgery. 8. 50–55. 42 indexed citations

8.

Calvert, Jacob, Qingqing Mao, Jana Hoffman, et al.. (2016). Using electronic health record collected clinical variables to predict medical intensive care unit mortality. Annals of Medicine and Surgery. 11. 52–57. 50 indexed citations

9.

Desautels, Thomas, Jaehoon Choe, Parag Gad, et al.. (2015). An Active Learning Algorithm for Control of Epidural Electrostimulation. IEEE Transactions on Biomedical Engineering. 62(10). 2443–2455. 11 indexed citations

10.

Desautels, Thomas, Andreas Krause, & Joel W. Burdick. (2012). Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization. Journal of Machine Learning Research. 15(1). 3873–3923. 38 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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