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Researcher · École Normale Supérieure de l'Enseignement Technique de Mohammedia · Morocco

Oumaima Terrada

Oumaima Terrada publishes mostly in Health Information Management, Artificial Intelligence and Information Systems, on topics such as Artificial Intelligence in Healthcare, Machine Learning in Healthcare and Imbalanced Data Classification Techniques.

ORCID 0000-0001-6250-4958 OpenAlex
World rank
#333,268
of 7,710,434 ranked researchers
Rank in Morocco
#161
of 14,526
Works
16
Citations
711
Citations per work
44.4
h-index
14
i10-index 14Top 18% in Health Information Management
Oumaima Terrada

What does Oumaima Terrada research?

Oumaima Terrada's work is mostly in Computer Science (43%), Health Professions (31%), Medicine (14%).

Health Sciences: 7 works · 45.7% of their workHealth Professions: 5 works · 31.4% of their workHealth Information Management: 5 works · 31.4% of their workMedicine: 2 works · 14.3% of their workRadiology, Nuclear Medicine and Imaging: 1 works · 8.6% of their workPhysiology: 1 works · 5.7% of their workPhysical Sciences: 7 works · 42.9% of their workComputer Science: 7 works · 42.9% of their workArtificial Intelligence: 5 works · 28.6% of their workInformation Systems: 1 works · 8.6% of their workComputer Vision and Pattern Recognition: 1 works · 5.7% of their workEverything else: 2 works · 11.4% of their workTHEIR WORKOumaima Terrada16works
Physical Sciences43%Health Sciences46%

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. Health Professions531.4%
    2. Medicine214.3%
    1. Computer Science742.9%
  3. Everything else211.4%
  1. 1Health Information Management31% of their works
  2. 2Artificial Intelligence29% of their works
  3. 3Information Systems9% of their works
  4. 4Radiology, Nuclear Medicine and Imaging9% of their works
  5. 5Computer Vision and Pattern Recognition6% of their works
  6. 6Physiology6% of their works

Research topics

Which keywords describe Oumaima Terrada's research?

The keywords of their largest research topics: Healthcare, Data Mining, Machine Learning, Big Data Analytics, Medical Diagnosis, Deep Learning, Electronic Health Records and Convolutional Neural Networks.

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 20 words, with their numbers
  1. Healthcare152 topics
  2. Data Mining132 topics
  3. Machine Learning132 topics
  4. Big Data Analytics111 topic
  5. Medical Diagnosis111 topic
  6. Deep Learning41 topic
  7. Electronic Health Records41 topic
  8. Convolutional Neural Networks32 topics
  9. Association Rules21 topic
  10. Classification21 topic
  11. Frequent Patterns21 topic
  12. Handwriting Recognition21 topic
  13. Imbalanced Data21 topic
  14. Parkinson's Disease21 topic
  15. Text Detection21 topic
  16. Voice Disorders21 topic
  17. Acoustic Modeling11 topic
  18. Deep Neural Networks11 topic
  19. Neural Machine Translation11 topic
  20. Statistical Machine Translation11 topic

Where does Oumaima Terrada work?

Oumaima Terrada's main affiliation in the publication record is École Normale Supérieure de l'Enseignement Technique de Mohammedia, Morocco.

How many publications and citations does Oumaima Terrada have?

OpenAlex counts 16 works and 711 citations for Oumaima Terrada, an h-index of 14, ranking #333,268 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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