Daniela Raicu

2.8k total citations
120 papers, 1.1k citations indexed

About

Daniela Raicu is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Daniela Raicu has authored 120 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Artificial Intelligence, 50 papers in Radiology, Nuclear Medicine and Imaging and 35 papers in Computer Vision and Pattern Recognition. Recurrent topics in Daniela Raicu's work include Radiomics and Machine Learning in Medical Imaging (38 papers), AI in cancer detection (34 papers) and Lung Cancer Diagnosis and Treatment (23 papers). Daniela Raicu is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (38 papers), AI in cancer detection (34 papers) and Lung Cancer Diagnosis and Treatment (23 papers). Daniela Raicu collaborates with scholars based in United States, Mexico and Australia. Daniela Raicu's co-authors include Jacob Furst, Dong-Hui Xu, David S. Channin, Samuel G. Armato, Noriko Tomuro, Yu Zhang, Katherine J. Strandburg, Jonathan Gemmell, Alexander Rasin and Samah Fodeh and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.

In The Last Decade

Daniela Raicu

107 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniela Raicu United States 17 470 444 343 242 119 120 1.1k
Shintami Chusnul Hidayati Indonesia 13 320 0.7× 255 0.6× 374 1.1× 208 0.9× 23 0.2× 71 952
G. Anthony Reina United States 9 329 0.7× 693 1.6× 94 0.3× 55 0.2× 42 0.4× 15 1.3k
I. Hutt United Kingdom 9 356 0.8× 821 1.8× 607 1.8× 127 0.5× 104 0.9× 9 1.1k
Bernard Gibaud France 18 315 0.7× 186 0.4× 288 0.8× 48 0.2× 154 1.3× 94 1.1k
Nikita Jain India 17 172 0.4× 424 1.0× 267 0.8× 36 0.1× 161 1.4× 85 1.3k
Jason Martin United States 7 333 0.7× 765 1.7× 96 0.3× 52 0.2× 42 0.4× 12 1.1k
Muhammad Imran Sharif Pakistan 15 225 0.5× 308 0.7× 364 1.1× 60 0.2× 17 0.1× 47 1.0k
Mathias Lux Austria 19 367 0.8× 498 1.1× 973 2.8× 125 0.5× 29 0.2× 102 1.8k
Maryam Panahiazar United States 14 142 0.3× 347 0.8× 109 0.3× 41 0.2× 166 1.4× 36 1.2k
Congcong Wang China 15 213 0.5× 187 0.4× 252 0.7× 25 0.1× 25 0.2× 73 750

Countries citing papers authored by Daniela Raicu

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Raicu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniela Raicu

This figure shows the co-authorship network connecting the top 25 collaborators of Daniela Raicu. A scholar is included among the top collaborators of Daniela Raicu 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 Daniela Raicu. Daniela Raicu 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.
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Rasin, Alexander, et al.. (2021). Ensemble Labeling towards Scientific Information Extraction (ELSIE)—Blob Extraction. 8. 11–20. 2 indexed citations
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Wang, Yiyang, Brian T. Soetikno, Jacob Furst, Daniela Raicu, & Amani A. Fawzi. (2019). Drusen diagnosis comparison between hyper-spectral and color retinal images. Biomedical Optics Express. 10(2). 914–914. 8 indexed citations
8.
León, Ana M., et al.. (2018). Automatic extraction of informal topics from online suicidal ideation. BMC Bioinformatics. 19(S8). 211–211. 26 indexed citations
9.
Cobb, Adrienne N., Taylor Erickson, Anai N. Kothari, et al.. (2018). Commercial quality “awards” are not a strong indicator of quality surgical care. Surgery. 164(3). 379–386. 2 indexed citations
10.
Rasin, Alexander, Eli T. Brown, Jacob Furst, et al.. (2017). An Integrated Database and Smart Search Tool for Medical Knowledge Extraction from Radiology Teaching Files. Knowledge Discovery and Data Mining. 10–18. 6 indexed citations
11.
Greenblum, Sharon, Max Krucoff, Jacob Furst, & Daniela Raicu. (2016). AUTOMATED IMAGE ANALYSIS OF NOISY MICROARRAYS. 371–375.
12.
Kothari, Anai N., Sarah A. Brownlee, Victor Chang, et al.. (2016). Characterizing the role of a high-volume cancer resection ecosystem on low-volume, high-quality surgical care. Surgery. 160(4). 839–849. 11 indexed citations
13.
Brandon, Christopher, et al.. (2015). Computational Methods for Tracking, Quantitative Assessment, and Visualization of C. elegans Locomotory Behavior. PLoS ONE. 10(12). e0145870–e0145870. 11 indexed citations
14.
Feigenbaum, Joan, et al.. (2011). Probabilistic lung nodule classification with belief decision trees. PubMed. 2011. 4493–4498. 23 indexed citations
15.
Peckham, Joan, Fatma Mili, Daniela Raicu, & Ingrid Russell. (2008). REUs: undergraduate research experiences and funding. Journal of computing sciences in colleges. 23(5). 208–211. 2 indexed citations
16.
Furst, Jacob, et al.. (2006). Single Organ Segmentation Filters for Multiple Organ Segmentation. PubMed. 2006. 3033–3036. 7 indexed citations
17.
Raicu, Daniela, et al.. (2006). Automatic Single-Organ Segmentation in Computed Tomography Images. 1081–1086. 10 indexed citations
18.
Strandburg, Katherine J. & Daniela Raicu. (2005). Privacy and Technologies of Identity: A Cross-Disciplinary Conversation. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 20 indexed citations
19.
Xu, Dong-Hui, et al.. (2004). RUN-LENGTH ENCODING FOR VOLUMETRIC TEXTURE. 83(16). 6063–4. 116 indexed citations
20.
Raicu, Daniela. (2003). A Data Mining Framework for Target Marketing.. Computers and Their Applications. 476–479. 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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