Diego Ardila

3.1k total citations · 2 hit papers
6 papers, 1.6k citations indexed

About

Diego Ardila is a scholar working on Pulmonary and Respiratory Medicine, Cognitive Neuroscience and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Diego Ardila has authored 6 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Pulmonary and Respiratory Medicine, 2 papers in Cognitive Neuroscience and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Diego Ardila's work include Radiomics and Machine Learning in Medical Imaging (2 papers), Neural dynamics and brain function (2 papers) and Face Recognition and Perception (2 papers). Diego Ardila is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (2 papers), Neural dynamics and brain function (2 papers) and Face Recognition and Perception (2 papers). Diego Ardila collaborates with scholars based in United States. Diego Ardila's co-authors include Daniel Tse, Joshua Reicher, Mozziyar Etemadi, Safal Shetty, Sujeeth Bharadwaj, Greg S. Corrado, Wenxing Ye, Lily Peng, Atilla P. Kiraly and David P. Naidich and has published in prestigious journals such as Nature Medicine, SHILAP Revista de lepidopterología and PLoS Computational Biology.

In The Last Decade

Diego Ardila

6 papers receiving 1.6k citations

Hit Papers

End-to-end lung cancer screening with three-dimens... 2014 2026 2018 2022 2019 2014 400 800 1.2k
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. End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography
    2019 1.2k citations Diego Ardila, Atilla P. Kiraly et al. Nature Medicine profile →
  2. Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition
    2014 391 citations Charles F. Cadieu, Ha Hong et al. PLoS Computational Biology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Diego Ardila United States 4 839 489 481 302 201 6 1.6k
Yaorong Ge United States 24 1.0k 1.2× 276 0.6× 630 1.3× 186 0.6× 327 1.6× 108 2.3k
William Speier United States 27 384 0.5× 464 0.9× 302 0.6× 412 1.4× 181 0.9× 90 1.8k
Corey Arnold United States 24 430 0.5× 657 1.3× 225 0.5× 193 0.6× 241 1.2× 105 1.7k
Ahmed Soliman United States 22 1.2k 1.5× 335 0.7× 516 1.1× 243 0.8× 345 1.7× 109 2.0k
Ken Chang United States 23 1.4k 1.7× 521 1.1× 336 0.7× 49 0.2× 169 0.8× 51 2.2k
Hari Trivedi United States 19 876 1.0× 509 1.0× 534 1.1× 62 0.2× 82 0.4× 68 1.9k
Claudia Mello‐Thoms Australia 26 1.3k 1.5× 1000 2.0× 704 1.5× 247 0.8× 308 1.5× 137 2.5k
Ahmed Elnakib United States 22 878 1.0× 347 0.7× 380 0.8× 238 0.8× 416 2.1× 104 1.6k
Jason Dowling Australia 24 1.7k 2.0× 381 0.8× 550 1.1× 62 0.2× 437 2.2× 129 2.7k
Michael Friebe Germany 17 316 0.4× 177 0.4× 223 0.5× 118 0.4× 92 0.5× 146 1.1k

Countries citing papers authored by Diego Ardila

Since Specialization
Citations

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

Fields of papers citing papers by Diego Ardila

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Diego Ardila

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

All Works

6 of 6 papers shown
1.
Weng, Wei‐Hung, Sebastien Baur, Christina Chen, et al.. (2024). Predicting cardiovascular disease risk using photoplethysmography and deep learning. SHILAP Revista de lepidopterología. 4(6). e0003204–e0003204. 6 indexed citations
2.
Ardila, Diego, Atilla P. Kiraly, Sujeeth Bharadwaj, et al.. (2019). End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nature Medicine. 25(6). 954–961. 1221 indexed citations breakdown →
3.
Ardila, Diego, Atilla P. Kiraly, Sujeeth Bharadwaj, et al.. (2018). Improving the specificity of lung cancer screening CT using deep learning. 1 indexed citations
4.
Roberts, Adam P., et al.. (2016). Audio Deepdream: Optimizing raw audio with convolutional networks. 12 indexed citations
5.
Cadieu, Charles F., Ha Hong, Daniel Yamins, et al.. (2014). Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition. PLoS Computational Biology. 10(12). e1003963–e1003963. 391 indexed citations breakdown →
6.
Cadieu, Charles F., Ha Hong, Daniel Yamins, et al.. (2014). Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition. DSpace@MIT (Massachusetts Institute of Technology). 1 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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Breakdown of academic impact, for papers by Yaorong Ge Breakdown of academic impact, for papers by William Speier Breakdown of academic impact, for papers by Corey Arnold Breakdown of academic impact, for papers by Ahmed Soliman Breakdown of academic impact, for papers by Ken Chang Breakdown of academic impact, for papers by Hari Trivedi Breakdown of academic impact, for papers by Claudia Mello‐Thoms Breakdown of academic impact, for papers by Ahmed Elnakib Breakdown of academic impact, for papers by Jason Dowling Breakdown of academic impact, for papers by Michael Friebe
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