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Researcher · Netherlands eScience Center · Netherlands

Candace Makeda Moore

Candace Makeda Moore publishes mostly in Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, on topics such as Radiomics and Machine Learning in Medical Imaging, AI in cancer detection and Medical Image Segmentation Techniques.

ORCID 0000-0003-1672-7565 OpenAlex
World rank
#2,137,524
of 7,710,434 ranked researchers
Rank in Netherlands
#46,148
of 107,149
Works
164
Citations
526
Citations per work
3.2
h-index
11
i10-index 11Top 37% in Artificial Intelligence
Candace Makeda Moore

What does Candace Makeda Moore research?

Candace Makeda Moore's work is mostly in Medicine (22%), Computer Science (13%).

Everything else: 107 works · 65.3% of their workHealth Sciences: 36 works · 21.9% of their workMedicine: 36 works · 21.9% of their workRadiology, Nuclear Medicine and Imaging: 11 works · 6.9% of their workPulmonary and Respiratory Medicine: 10 works · 6.2% of their workSurgery: 8 works · 4.9% of their workEpidemiology: 6 works · 3.9% of their workPhysical Sciences: 21 works · 12.8% of their workComputer Science: 21 works · 12.8% of their workArtificial Intelligence: 13 works · 7.9% of their workComputer Vision and Pattern Recognition: 8 works · 4.9% of their workTHEIR WORKCandace MakedaMoore164works
Physical Sciences13%Health Sciences22%

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. Everything else10765.3%
    1. Medicine3621.9%
    1. Computer Science2112.8%
  1. 1Artificial Intelligence8% of their works
  2. 2Radiology, Nuclear Medicine and Imaging7% of their works
  3. 3Pulmonary and Respiratory Medicine6% of their works
  4. 4Computer Vision and Pattern Recognition5% of their works
  5. 5Surgery5% of their works
  6. 6Epidemiology4% of their works

Research topics

Which keywords describe Candace Makeda Moore's research?

The keywords of their largest research topics: Deep Learning, Machine Learning, Medical Imaging, Precision Medicine, Feature Extraction, Medical Image Analysis, Quantitative Analysis and Radiomics.

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 Learning225 topics
  2. Machine Learning223 topics
  3. Medical Imaging162 topics
  4. Precision Medicine162 topics
  5. Feature Extraction132 topics
  6. Medical Image Analysis122 topics
  7. Quantitative Analysis101 topic
  8. Radiomics101 topic
  9. Neural Networks72 topics
  10. Artificial Intelligence61 topic
  11. Computer-Aided Detection61 topic
  12. Graph Cuts61 topic
  13. Healthcare61 topic
  14. Histopathology Images61 topic
  15. Image Segmentation61 topic
  16. Time Series62 topics
  17. Backpropagation Learning41 topic
  18. Self-Organizing Maps41 topic
  19. Adaptive Designs31 topic
  20. Anomaly Detection31 topic
  21. Clustering31 topic
  22. Dynamic Time Warping31 topic
  23. False Discovery Rate31 topic
  24. Unsupervised31 topic

Where does Candace Makeda Moore work?

Candace Makeda Moore's main affiliation in the publication record is Netherlands eScience Center, Netherlands.

How many publications and citations does Candace Makeda Moore have?

OpenAlex counts 164 works and 526 citations for Candace Makeda Moore, an h-index of 11, ranking #2,137,524 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.

Discussion

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