André Carrington

607 total citations
8 papers, 352 citations indexed

About

André Carrington is a scholar working on Artificial Intelligence, General Health Professions and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, André Carrington has authored 8 papers receiving a total of 352 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in General Health Professions and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in André Carrington's work include Radiomics and Machine Learning in Medical Imaging (1 paper), Clinical practice guidelines implementation (1 paper) and Fetal and Pediatric Neurological Disorders (1 paper). André Carrington is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (1 paper), Clinical practice guidelines implementation (1 paper) and Fetal and Pediatric Neurological Disorders (1 paper). André Carrington collaborates with scholars based in Canada, Austria and United States. André Carrington's co-authors include Andreas Holzinger, Heimo Müller, Helen Chen, Paul Fieguth, Douglas G. Manuel, Richard I. Aviv, Steven Hawken, Ruth Rennicks White, Malia S. Q. Murphy and Alysha L. J. Dingwall‐Harvey and has published in prestigious journals such as PLoS ONE, BMC Medical Informatics and Decision Making and Multiple Sclerosis and Related Disorders.

In The Last Decade

André Carrington

4 papers receiving 342 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
André Carrington Canada 3 203 100 59 38 24 8 352
Anna Markella Antoniadi Ireland 9 248 1.2× 157 1.6× 61 1.0× 27 0.7× 17 0.7× 12 499
Zhiyu Wan United States 11 240 1.2× 82 0.8× 33 0.6× 26 0.7× 10 0.4× 40 450
Francisco Maria Calisto Portugal 8 184 0.9× 119 1.2× 85 1.4× 29 0.8× 36 1.5× 9 340
Boris Babic United States 7 133 0.7× 229 2.3× 64 1.1× 75 2.0× 8 0.3× 16 464
Michaela Th. Mayrhofer Netherlands 10 83 0.4× 86 0.9× 29 0.5× 22 0.6× 6 0.3× 28 325
Helen Frazer Australia 11 189 0.9× 187 1.9× 143 2.4× 37 1.0× 19 0.8× 30 498
Nicolás Nieto Argentina 3 139 0.7× 160 1.6× 130 2.2× 29 0.8× 27 1.1× 8 405
Agostina J. Larrazabal Argentina 2 131 0.6× 160 1.6× 137 2.3× 29 0.8× 33 1.4× 5 380
Cecilia Panigutti Italy 6 206 1.0× 102 1.0× 12 0.2× 49 1.3× 15 0.6× 7 346
Benjamin Kompa United States 6 128 0.6× 76 0.8× 59 1.0× 14 0.4× 23 1.0× 8 338

Countries citing papers authored by André Carrington

Since Specialization
Citations

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

Fields of papers citing papers by André Carrington

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of André Carrington

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

All Works

8 of 8 papers shown
1.
2.
Thebault, Simon, Gerd Melkus, Angela M. Auriat, et al.. (2023). MRI graph parameters are longitudinal markers of neuronal integrity in multiple sclerosis. Multiple Sclerosis and Related Disorders. 80. 105066–105066.
3.
Zhang, Liying, André Carrington, Rebecca E. Thornhill, et al.. (2023). Clinical Features, Non-Contrast CT Radiomic and Radiological Signs in Models for the Prediction of Hematoma Expansion in Intracerebral Hemorrhage. Canadian Association of Radiologists Journal. 74(4). 713–722.
4.
Walker, Mark, Malia S. Q. Murphy, Darine El‐Chaâr, et al.. (2022). Using deep-learning in fetal ultrasound analysis for diagnosis of cystic hygroma in the first trimester. PLoS ONE. 17(6). e0269323–e0269323. 16 indexed citations
5.
Holzinger, Andreas, André Carrington, & Heimo Müller. (2020). Measuring the Quality of Explanations: The System Causability Scale (SCS). KI - Künstliche Intelligenz. 34(2). 193–198. 216 indexed citations
6.
Carrington, André, et al.. (2020). A new concordant partial AUC and partial c statistic for imbalanced data in the evaluation of machine learning algorithms. BMC Medical Informatics and Decision Making. 20(1). 4–4. 118 indexed citations
7.
Carrington, André, et al.. (2020). LO22: Risk-stratification of emergency department syncope by artificial intelligence using machine learning: human, statistics or machine. Canadian Journal of Emergency Medicine. 22(S1). S15–S15.
8.
Carrington, André, Paul Fieguth, & Helen Chen. (2014). A new Mercer sigmoid kernel for clinical data classification. PubMed. 2014. 6397–6401. 2 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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