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Researcher · Icometrix (Belgium) · Belgium

Ezequiel de la Rosa

Ezequiel de la Rosa publishes mostly in Epidemiology, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, on topics such as Acute Ischemic Stroke Management, Brain Tumor Detection and Classification and Medical Image Segmentation Techniques.

ORCID 0000-0002-9042-1962 OpenAlex
World rank
#1,884,104
of 7,710,434 ranked researchers
Rank in Belgium
#17,266
of 67,186
Works
70
Citations
843
Citations per work
12.0
h-index
14
i10-index 15Top 39% in Epidemiology
Ezequiel de la Rosa

What does Ezequiel de la Rosa research?

Ezequiel de la Rosa's work is mostly in Medicine (38%), Computer Science (14%), Neuroscience (11%).

Health Sciences: 26 works · 37.5% of their workMedicine: 26 works · 37.5% of their workEpidemiology: 12 works · 17.7% of their workRadiology, Nuclear Medicine and Imaging: 8 works · 11.3% of their workCardiology and Cardiovascular Medicine: 6 works · 8.5% of their workEverything else: 19 works · 27.1% of their workPhysical Sciences: 17 works · 24.8% of their workComputer Science: 10 works · 14.2% of their workComputer Vision and Pattern Recognition: 10 works · 14.2% of their workEngineering: 7 works · 10.6% of their workBiomedical Engineering: 7 works · 10.6% of their workLife Sciences: 7 works · 10.6% of their workNeuroscience: 7 works · 10.6% of their workNeurology: 7 works · 10.6% of their workTHEIR WORKEzequiel de laRosa70works
Life Sciences11%Physical Sciences25%Health Sciences38%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Medicine2637.5%
  2. Everything else1927.1%
    1. Computer Science1014.2%
    2. Engineering710.6%
    1. Neuroscience710.6%
  1. 1Epidemiology18% of their works
  2. 2Computer Vision and Pattern Recognition14% of their works
  3. 3Radiology, Nuclear Medicine and Imaging11% of their works
  4. 4Neurology11% of their works
  5. 5Biomedical Engineering11% of their works
  6. 6Cardiology and Cardiovascular Medicine8% of their works

Research topics

Which keywords describe Ezequiel de la Rosa's research?

The keywords of their largest research topics: Deep Learning, Image Segmentation, Machine Learning, Medical Image Analysis, Feature Extraction, Medical Imaging, Ischemic Stroke and Thrombolysis.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 24 words, with their numbers
  1. Deep Learning455 topics
  2. Image Segmentation262 topics
  3. Machine Learning263 topics
  4. Medical Image Analysis243 topics
  5. Feature Extraction212 topics
  6. Medical Imaging212 topics
  7. Ischemic Stroke201 topic
  8. Thrombolysis201 topic
  9. Texture Analysis172 topics
  10. Brain Tumor151 topic
  11. MRI151 topic
  12. Active Contours111 topic
  13. Convolutional Neural Networks112 topics
  14. Graph Cuts111 topic
  15. Spine Segmentation81 topic
  16. Vertebrae Detection81 topic
  17. Carotid Artery Stenosis61 topic
  18. Endarterectomy61 topic
  19. Image Recognition61 topic
  20. Object Detection61 topic
  21. Quantitative Analysis61 topic
  22. Radiomics61 topic
  23. Computer-Aided Detection51 topic
  24. Histopathology Images51 topic

Where does Ezequiel de la Rosa work?

Ezequiel de la Rosa's main affiliation in the publication record is Icometrix (Belgium), Belgium.

How many publications and citations does Ezequiel de la Rosa have?

OpenAlex counts 70 works and 843 citations for Ezequiel de la Rosa, an h-index of 14, ranking #1,884,104 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

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