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Researcher · Benha University · Egypt

Shaker El–Sappagh

Shaker El–Sappagh publishes mostly in Artificial Intelligence, Health Information Management and Molecular Biology, on topics such as Artificial Intelligence in Healthcare, Machine Learning in Healthcare and Biomedical Text Mining and Ontologies.

ORCID 0000-0001-9705-1477 OpenAlex
World rank
#23,976
of 7,710,434 ranked researchers
Rank in Egypt
#56
of 36,277
Works
181
Citations
10k
Citations per work
56.3
h-index
51
i10-index 114Top 0.9% in Artificial Intelligence
Shaker El–Sappagh

What does Shaker El–Sappagh research?

Shaker El–Sappagh's work is mostly in Computer Science (47%), Health Professions (9%), Biochemistry, Genetics and Molecular Biology (7%).

Physical Sciences: 85 works · 47.0% of their workComputer Science: 85 works · 47.0% of their workArtificial Intelligence: 56 works · 30.8% of their workComputer Vision and Pattern Recognition: 11 works · 6.0% of their workInformation Systems: 9 works · 5.2% of their workComputer Networks and Communications: 9 works · 5.0% of their workEverything else: 66 works · 36.7% of their workHealth Sciences: 16 works · 8.9% of their workHealth Professions: 16 works · 8.9% of their workHealth Information Management: 16 works · 8.9% of their workLife Sciences: 13 works · 7.4% of their workBiochemistry, Genetics and Molecular Biology: 13 works · 7.4% of their workMolecular Biology: 13 works · 7.4% of their workTHEIR WORKShaker El–Sappagh181works
Life Sciences7%Physical Sciences47%Health Sciences9%

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. Computer Science8547.0%
  2. Everything else6636.7%
    1. Health Professions168.9%
    1. Biochemistry, Genetics and Molecular Biology137.4%
  1. 1Artificial Intelligence31% of their works
  2. 2Health Information Management9% of their works
  3. 3Molecular Biology7% of their works
  4. 4Computer Vision and Pattern Recognition6% of their works
  5. 5Information Systems5% of their works
  6. 6Computer Networks and Communications5% of their works

Research topics

Which keywords describe Shaker El–Sappagh's research?

The keywords of their largest research topics: Deep Learning, Healthcare, Machine Learning, Data Integration, Semantic Web, Big Data Analytics, Medical Diagnosis and Electronic Health Records.

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.

All 24 words, with their numbers
  1. Deep Learning784 topics
  2. Healthcare782 topics
  3. Machine Learning683 topics
  4. Data Integration592 topics
  5. Semantic Web592 topics
  6. Big Data Analytics411 topic
  7. Medical Diagnosis411 topic
  8. Electronic Health Records371 topic
  9. Predictive Modeling371 topic
  10. Biomedical Ontologies301 topic
  11. Text Mining301 topic
  12. Linked Data291 topic
  13. Ontology291 topic
  14. Convolutional Neural Networks282 topics
  15. Medical Imaging272 topics
  16. Transfer Learning272 topics
  17. COVID-19141 topic
  18. Chest X-Ray141 topic
  19. Histopathology Images141 topic
  20. Medical Image Analysis141 topic
  21. Brain Tumor131 topic
  22. MRI131 topic
  23. Alzheimer's Disease111 topic
  24. Mild Cognitive Impairment111 topic

Where does Shaker El–Sappagh work?

Shaker El–Sappagh's main affiliation in the publication record is Benha University, Egypt.

How many publications and citations does Shaker El–Sappagh have?

OpenAlex counts 181 works and 10,192 citations for Shaker El–Sappagh, an h-index of 51, ranking #23,976 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised 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.

Other researchers named Shaker El–Sappagh

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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