Roselyne Tchoua

452 total citations
31 papers, 272 citations indexed

About

Roselyne Tchoua is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Roselyne Tchoua has authored 31 papers receiving a total of 272 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 9 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Molecular Biology. Recurrent topics in Roselyne Tchoua's work include Radiomics and Machine Learning in Medical Imaging (6 papers), Biomedical Text Mining and Ontologies (6 papers) and Topic Modeling (6 papers). Roselyne Tchoua is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (6 papers), Biomedical Text Mining and Ontologies (6 papers) and Topic Modeling (6 papers). Roselyne Tchoua collaborates with scholars based in United States, Australia and Netherlands. Roselyne Tchoua's co-authors include Kyle Chard, Juan Pablo, Jay Lofstead, Ian Foster, Debra J. Audus, Jeremy Logan, Scott Klasky, Manish Parashar, Matthew Wolf and Qing Liu and has published in prestigious journals such as BMC Medical Research Methodology, Computational Materials Science and Journal of Chemical Education.

In The Last Decade

Roselyne Tchoua

22 papers receiving 266 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Roselyne Tchoua United States 7 123 53 52 46 44 31 272
Dmitry Duplyakin United States 9 190 1.5× 63 1.2× 15 0.3× 48 1.0× 30 0.7× 30 338
Tomasz Piontek Poland 10 148 1.2× 19 0.4× 38 0.7× 77 1.7× 18 0.4× 18 243
G Kumfert United States 8 117 1.0× 29 0.5× 58 1.1× 71 1.5× 9 0.2× 12 212
Arthur Trew United Kingdom 10 96 0.8× 51 1.0× 19 0.4× 39 0.8× 17 0.4× 39 294
Joris Borgdorff Netherlands 10 111 0.9× 4 0.1× 70 1.3× 27 0.6× 29 0.7× 15 264
Vernon Austel United States 9 74 0.6× 91 1.7× 5 0.1× 70 1.5× 15 0.3× 11 256
Arthur S Buddy Bland United States 6 178 1.4× 33 0.6× 16 0.3× 110 2.4× 14 0.3× 9 272
Justin Luitjens United States 10 162 1.3× 34 0.6× 7 0.1× 179 3.9× 23 0.5× 16 308
David Snelling United Kingdom 10 186 1.5× 37 0.7× 84 1.6× 54 1.2× 10 0.2× 30 285
Sunita Chandrasekaran United States 9 143 1.2× 16 0.3× 12 0.2× 138 3.0× 8 0.2× 49 249

Countries citing papers authored by Roselyne Tchoua

Since Specialization
Citations

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

Fields of papers citing papers by Roselyne Tchoua

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roselyne Tchoua

This figure shows the co-authorship network connecting the top 25 collaborators of Roselyne Tchoua. A scholar is included among the top collaborators of Roselyne Tchoua 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 Roselyne Tchoua. Roselyne Tchoua 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
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Wang, Yiyang, Jacob Furst, Daniela Raicu, et al.. (2024). Outcome risk model development for heterogeneity of treatment effect analyses: a comparison of non-parametric machine learning methods and semi-parametric statistical methods. BMC Medical Research Methodology. 24(1). 158–158. 2 indexed citations
3.
Raicu, Daniela, et al.. (2024). 318 Discovering Subgroups with Supervised Machine Learning Models for Heterogeneity of Treatment Effect Analysis. Journal of Clinical and Translational Science. 8(s1). 97–98.
4.
Raicu, Daniela, et al.. (2024). Leveraging Community Health Workers for Predicting Emergency Department Readmissions. International Journal of Semantic Computing. 1–21.
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Furst, Jacob, et al.. (2023). Iterative K-means clustering for disease subtype discovery. 85–85.
8.
Wang, Yiyang, et al.. (2023). Optimizing Computer-Aided Diagnosis with Cost-Aware Deep Learning Models. PubMed. 29. 108–119. 2 indexed citations
9.
Rasin, Alexander, Roselyne Tchoua, Jacob Furst, et al.. (2023). Biomedical heterogeneous data categorization and schema mapping toward data integration. Frontiers in Big Data. 6. 1173038–1173038. 1 indexed citations
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Wang, Yiyang, et al.. (2022). Human-in-the-loop deep learning retinal image classification with customized loss function. 11601. 94–94. 1 indexed citations
12.
Tchoua, Roselyne, et al.. (2022). Failure Sources in Machine Learning for Medicine—A Study. Zenodo (CERN European Organization for Nuclear Research). 501–506. 1 indexed citations
13.
Rasin, Alexander, et al.. (2021). Ensemble Labeling towards Scientific Information Extraction (ELSIE)—Blob Extraction. 8. 11–20. 2 indexed citations
14.
Furst, Jacob, et al.. (2020). Learning Latent Spiculated Features for Lung Nodule Characterization. PubMed. 2020. 1254–1257. 5 indexed citations
15.
Tchoua, Roselyne, Logan Ward, Kyle Chard, et al.. (2019). Active Learning Yields Better Training Data for Scientific Named Entity Recognition. 126–135. 9 indexed citations
16.
Tchoua, Roselyne, Logan Ward, Kyle Chard, et al.. (2018). Towards hybrid human-machine scientific information extraction. 6. 1–3. 3 indexed citations
17.
Tchoua, Roselyne, Kyle Chard, Debra J. Audus, et al.. (2016). A Hybrid Human-computer Approach to the Extraction of Scientific Facts from the Literature. Procedia Computer Science. 80. 386–397. 17 indexed citations
18.
Tchoua, Roselyne, Jian Qin, Debra J. Audus, et al.. (2016). Blending Education and Polymer Science: Semiautomated Creation of a Thermodynamic Property Database. Journal of Chemical Education. 93(9). 1561–1568. 19 indexed citations
19.
Tchoua, Roselyne, Hasan Abbasi, Scott Klasky, et al.. (2012). Collaborative monitoring and visualization of HPC data. 6. 397–403. 1 indexed citations
20.
Tchoua, Roselyne, Scott Klasky, Norbert Podhorszki, et al.. (2010). Collaborative monitoring and analysis for simulation scientists. 20. 235–244. 3 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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