Constanza L. Andaur Navarro

5.2k total citations · 2 hit papers
18 papers, 1.1k citations indexed

About

Constanza L. Andaur Navarro is a scholar working on Health Informatics, Statistics, Probability and Uncertainty and Artificial Intelligence. According to data from OpenAlex, Constanza L. Andaur Navarro has authored 18 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Health Informatics, 8 papers in Statistics, Probability and Uncertainty and 7 papers in Artificial Intelligence. Recurrent topics in Constanza L. Andaur Navarro's work include Artificial Intelligence in Healthcare and Education (12 papers), Meta-analysis and systematic reviews (8 papers) and Machine Learning in Healthcare (6 papers). Constanza L. Andaur Navarro is often cited by papers focused on Artificial Intelligence in Healthcare and Education (12 papers), Meta-analysis and systematic reviews (8 papers) and Machine Learning in Healthcare (6 papers). Constanza L. Andaur Navarro collaborates with scholars based in Netherlands, United Kingdom and Belgium. Constanza L. Andaur Navarro's co-authors include Jie Ma, Gary S. Collins, Lotty Hooft, Paula Dhiman, Richard D Riley, Karel G.M. Moons, Ben Van Calster, Johanna AAG Damen, Maarten van Smeden and Toshihiko Takada and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Nutrition and BMJ.

In The Last Decade

Constanza L. Andaur Navarro

15 papers receiving 1.1k citations

Hit Papers

Protocol for development of a reporting guideline (TRIPOD... 2021 2026 2022 2024 2021 2021 100 200 300 400
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.

  1. Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence
    2021 475 citations Gary S. Collins, Paula Dhiman et al. BMJ Open profile →
  2. Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review
    2021 222 citations Constanza L. Andaur Navarro, Johanna AAG Damen et al. BMJ profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Constanza L. Andaur Navarro Netherlands 12 436 367 306 136 110 18 1.1k
Steven W J Nijman Netherlands 9 276 0.6× 304 0.8× 157 0.5× 118 0.9× 107 1.0× 10 890
Patrícia Logullo United Kingdom 10 223 0.5× 153 0.4× 179 0.6× 82 0.6× 40 0.4× 26 895
Toshihiko Takada Japan 16 164 0.4× 170 0.5× 114 0.4× 138 1.0× 54 0.5× 74 924
Jason Hom United States 22 327 0.8× 268 0.7× 386 1.3× 458 3.4× 138 1.3× 66 1.7k
Jamil S. Samaan United States 15 523 1.2× 228 0.6× 237 0.8× 87 0.6× 27 0.2× 48 1.1k
Stan Benjamens Netherlands 13 403 0.9× 209 0.6× 272 0.9× 57 0.4× 63 0.6× 35 978
Valentina Bellini Italy 15 709 1.6× 359 1.0× 328 1.1× 40 0.3× 57 0.5× 63 1.3k
Suresh Balu United States 16 446 1.0× 374 1.0× 158 0.5× 204 1.5× 206 1.9× 54 1.1k
Katherine McAllister United Kingdom 9 149 0.3× 117 0.3× 120 0.4× 107 0.8× 55 0.5× 11 754

Countries citing papers authored by Constanza L. Andaur Navarro

Since Specialization
Citations

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

Fields of papers citing papers by Constanza L. Andaur Navarro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Constanza L. Andaur Navarro. 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 Constanza L. Andaur Navarro. The network helps show where Constanza L. Andaur Navarro may publish in the future.

Co-authorship network of co-authors of Constanza L. Andaur Navarro

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

All Works

18 of 18 papers shown
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Navarro, Constanza L. Andaur, Johanna AAG Damen, Mona Ghannad, et al.. (2024). SPIN-PM: a consensus framework to evaluate the presence of spin in studies on prediction models. Journal of Clinical Epidemiology. 170. 111364–111364.
4.
Levis, Brooke, Kym I E Snell, Johanna AAG Damen, et al.. (2023). Risk of bias assessments in individual participant data meta-analyses of test accuracy and prediction models: a review shows improvements are needed. Journal of Clinical Epidemiology. 165. 111206–111206. 1 indexed citations
5.
Navarro, Constanza L. Andaur, et al.. (2023). Dementia prediction in the general population using clinically accessible variables: a proof-of-concept study using machine learning. The AGES-Reykjavik study. BMC Medical Informatics and Decision Making. 23(1). 168–168. 11 indexed citations
6.
Dhiman, Paula, Jie Ma, Constanza L. Andaur Navarro, et al.. (2023). Overinterpretation of findings in machine learning prediction model studies in oncology: a systematic review. Journal of Clinical Epidemiology. 157. 120–133. 22 indexed citations
7.
Navarro, Constanza L. Andaur, Johanna AAG Damen, Toshihiko Takada, et al.. (2023). Systematic review finds “spin” practices and poor reporting standards in studies on machine learning-based prediction models. Journal of Clinical Epidemiology. 158. 99–110. 34 indexed citations
8.
Dhiman, Paula, Jie Ma, Constanza L. Andaur Navarro, et al.. (2022). Risk of bias of prognostic models developed using machine learning: a systematic review in oncology. SHILAP Revista de lepidopterología. 6(1). 13–13. 36 indexed citations
9.
Navarro, Constanza L. Andaur, Johanna AAG Damen, Maarten van Smeden, et al.. (2022). Systematic review identifies the design and methodological conduct of studies on machine learning-based prediction models. Journal of Clinical Epidemiology. 154. 8–22. 58 indexed citations
10.
Navarro, Constanza L. Andaur, Johanna AAG Damen, Toshihiko Takada, et al.. (2022). Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review. BMC Medical Research Methodology. 22(1). 12–12. 73 indexed citations
11.
Dhiman, Paula, Jie Ma, Constanza L. Andaur Navarro, et al.. (2022). Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review. BMC Medical Research Methodology. 22(1). 101–101. 68 indexed citations
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Navarro, Constanza L. Andaur, Johanna AAG Damen, Toshihiko Takada, et al.. (2021). Completeness of reporting of clinical prediction models developed using supervised machine learning: A systematic review. medRxiv. 8 indexed citations
14.
Navarro, Constanza L. Andaur, Johanna AAG Damen, Toshihiko Takada, et al.. (2021). Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review. BMJ. 375. n2281–n2281. 222 indexed citations breakdown →
15.
Collins, Gary S., Paula Dhiman, Constanza L. Andaur Navarro, et al.. (2021). Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence. BMJ Open. 11(7). e048008–e048008. 475 indexed citations breakdown →
16.
Dhiman, Paula, Jie Ma, Constanza L. Andaur Navarro, et al.. (2021). Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved. Journal of Clinical Epidemiology. 138. 60–72. 71 indexed citations
17.
Navarro, Constanza L. Andaur, Katerina Trajanoska, Fernando Rivadeneira, et al.. (2021). Associations Between Prenatal, Perinatal, and Early Childhood Vitamin D Status and Risk of Dental Caries at 6 Years. Journal of Nutrition. 151(7). 1993–2000. 19 indexed citations
18.
Navarro, Constanza L. Andaur, Johanna AAG Damen, Toshihiko Takada, et al.. (2020). Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques. BMJ Open. 10(11). e038832–e038832. 41 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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