Davy van de Sande

756 total citations
17 papers, 394 citations indexed

About

Davy van de Sande is a scholar working on Health Informatics, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Davy van de Sande has authored 17 papers receiving a total of 394 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Health Informatics, 8 papers in Artificial Intelligence and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Davy van de Sande's work include Artificial Intelligence in Healthcare and Education (9 papers), Machine Learning in Healthcare (5 papers) and COVID-19 diagnosis using AI (4 papers). Davy van de Sande is often cited by papers focused on Artificial Intelligence in Healthcare and Education (9 papers), Machine Learning in Healthcare (5 papers) and COVID-19 diagnosis using AI (4 papers). Davy van de Sande collaborates with scholars based in Netherlands, United States and Germany. Davy van de Sande's co-authors include Michel E. van Genderen, Diederik Gommers, Jasper van Bommel, Joost Huiskens, Howard J. Ansel, William F. Prigge, Scott R. Ketover, R L Gebhard, Francis J. Peterson and Jacob J. Visser and has published in prestigious journals such as Hepatology, Intensive Care Medicine and Critical Care.

In The Last Decade

Davy van de Sande

16 papers receiving 385 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Davy van de Sande Netherlands 8 152 116 111 90 78 17 394
Chenxi Huang United States 11 80 0.5× 100 0.9× 93 0.8× 100 1.1× 66 0.8× 39 600
Samson Mataraso United States 10 109 0.7× 52 0.4× 219 2.0× 218 2.4× 149 1.9× 22 559
Pattharawin Pattharanitima Thailand 14 49 0.3× 130 1.1× 52 0.5× 116 1.3× 35 0.4× 57 607
Anna Siefkas United States 9 46 0.3× 36 0.3× 81 0.7× 72 0.8× 94 1.2× 17 325
H.M. Giannini United States 4 71 0.5× 44 0.4× 164 1.5× 194 2.2× 29 0.4× 8 340
Jennifer C. Ginestra United States 6 73 0.5× 52 0.4× 181 1.6× 216 2.4× 30 0.4× 16 366
Adrian Goudie Australia 14 79 0.5× 195 1.7× 31 0.3× 61 0.7× 177 2.3× 27 575
Renata R. Almeida United States 11 56 0.4× 45 0.4× 22 0.2× 53 0.6× 119 1.5× 22 348
Nathan Brajer United States 5 160 1.1× 27 0.2× 157 1.4× 111 1.2× 72 0.9× 5 384
Alyssa T. Watanabe United States 9 54 0.4× 92 0.8× 114 1.0× 31 0.3× 140 1.8× 18 330

Countries citing papers authored by Davy van de Sande

Since Specialization
Citations

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

Fields of papers citing papers by Davy van de Sande

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Davy van de Sande. 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 Davy van de Sande. The network helps show where Davy van de Sande may publish in the future.

Co-authorship network of co-authors of Davy van de Sande

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

All Works

17 of 17 papers shown
1.
Brand, Jan A.J.G. van den, Davy van de Sande, Marianne de Vries, et al.. (2025). Leveraging GPT-4 enables patient comprehension of radiology reports. European Journal of Radiology. 187. 112111–112111. 1 indexed citations
2.
Sande, Davy van de, et al.. (2025). Comparative evaluation and performance of large language models on expert level critical care questions: a benchmark study. Critical Care. 29(1). 72–72. 8 indexed citations
3.
Sande, Davy van de, et al.. (2025). Bridging the gap: a practical step-by-step approach to warrant safe implementation of large language models in healthcare. Frontiers in Artificial Intelligence. 8. 1504805–1504805. 5 indexed citations
4.
Sande, Davy van de, Freek Daams, Diederik Gommers, et al.. (2025). Importance of model governance in clinical AI models: case study on the relevance of data drift detection. EUR Research Repository (Erasmus University Rotterdam). 1(1). e000046–e000046. 1 indexed citations
5.
Sande, Davy van de, Denise E. Hilling, Christian Jung, et al.. (2025). Operationalization of Artificial Intelligence Applications in the Intensive Care Unit. JAMA Network Open. 8(7). e2522866–e2522866. 4 indexed citations
6.
Genderen, Michel E. van, Davy van de Sande, Maurizio Cecconi, & Christian Jung. (2024). Federated learning: a step in the right direction to improve data equity. Intensive Care Medicine. 50(8). 1393–1394. 2 indexed citations
7.
Genderen, Michel E. van, Davy van de Sande, Lotty Hooft, et al.. (2024). Charting a new course in healthcare: early-stage AI algorithm registration to enhance trust and transparency. npj Digital Medicine. 7(1). 119–119. 6 indexed citations
8.
Sande, Davy van de, et al.. (2024). To warrant clinical adoption AI models require a multi-faceted implementation evaluation. npj Digital Medicine. 7(1). 58–58. 12 indexed citations
9.
Sande, Davy van de, Michel E. van Genderen, Cornelis Verhoef, et al.. (2022). Optimizing discharge after major surgery using an artificial intelligence–based decision support tool (DESIRE): An external validation study. Surgery. 172(2). 663–669. 10 indexed citations
10.
Sande, Davy van de, Michel E. van Genderen, Joost Huiskens, et al.. (2022). Developing, implementing and governing artificial intelligence in medicine: a step-by-step approach to prevent an artificial intelligence winter. BMJ Health & Care Informatics. 29(1). e100495–e100495. 76 indexed citations
11.
Schoenmakers, Sam, Johannes J. Duvekot, Diederik Gommers, et al.. (2022). Gravid uterine torsion after prone positioning in SARS-CoV2 (COVID-19)-related acute respiratory distress syndrome. Journal of Surgical Case Reports. 2022(6). rjac289–rjac289.
12.
Sande, Davy van de, Michel E. van Genderen, Joost Huiskens, Diederik Gommers, & Jasper van Bommel. (2021). Moving from bytes to bedside: a systematic review on the use of artificial intelligence in the intensive care unit. Intensive Care Medicine. 47(7). 750–760. 143 indexed citations
13.
Sande, Davy van de, Michel E. van Genderen, Cornelis Verhoef, et al.. (2021). Predicting need for hospital-specific interventional care after surgery using electronic health record data. Surgery. 170(3). 790–796. 8 indexed citations
14.
Sande, Davy van de, et al.. (2021). Generating insights in uncharted territories: real-time learning from data in critically ill patients–an implementer report. BMJ Health & Care Informatics. 28(1). e100447–e100447. 1 indexed citations
15.
Sande, Davy van de, Michel E. van Genderen, Henrik Endeman, et al.. (2020). Predicting thromboembolic complications in COVID-19 ICU patients using machine learning. Journal of Clinical and Translational Research. 6(4). 179–186. 6 indexed citations
16.
Anibarro, Luis, et al.. (2010). Treatment completion in latent tuberculosis infection at specialist tuberculosis units in Spain.. PubMed. 14(6). 701–7. 32 indexed citations
17.
Gebhard, R L, William F. Prigge, Howard J. Ansel, et al.. (1996). The Role of Gallbladder Emptying in Gallstone Formation During Diet–Induced Rapid Weight Loss. Hepatology. 24(3). 544–548. 79 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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