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Researcher · Robert Morris University · United States

Tabitha Chukwudi Aghaunor

Tabitha Chukwudi Aghaunor publishes mostly in Artificial Intelligence, Information Systems and Computer Networks and Communications, on topics such as Artificial Intelligence in Healthcare, Network Security and Intrusion Detection and AI in cancer detection.

ORCID 0009-0008-0249-9016 OpenAlex
World rank
#2,007,806
of 7,710,434 ranked researchers
Rank in United States
#609,336
of 1,627,098
Works
26
Citations
64
Citations per work
2.5
h-index
5
i10-index 3Top 82% in Artificial Intelligence
Tabitha Chukwudi Aghaunor

What does Tabitha Chukwudi Aghaunor research?

Tabitha Chukwudi Aghaunor's work is mostly in Computer Science (46%), Health Professions (8%), Engineering (6%).

Physical Sciences: 13 works · 51.6% of their workComputer Science: 12 works · 45.5% of their workArtificial Intelligence: 5 works · 18.2% of their workInformation Systems: 4 works · 16.7% of their workComputer Networks and Communications: 3 works · 10.6% of their workEngineering: 2 works · 6.1% of their workElectrical and Electronic Engineering: 2 works · 6.1% of their workEverything else: 9 works · 36.3% of their workHealth Sciences: 2 works · 7.6% of their workHealth Professions: 2 works · 7.6% of their workHealth Information Management: 2 works · 7.6% of their workSocial Sciences: 1 works · 4.5% of their workSocial Sciences: 1 works · 4.5% of their workEducation: 1 works · 4.5% of their workTHEIR WORKTabitha ChukwudiAghaunor26works
Physical Sciences52%Health Sciences8%Social Sciences4%

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 Science1245.5%
    2. Engineering26.1%
  2. Everything else936.3%
    1. Health Professions27.6%
    1. Social Sciences14.5%
  1. 1Artificial Intelligence18% of their works
  2. 2Information Systems17% of their works
  3. 3Computer Networks and Communications11% of their works
  4. 4Health Information Management8% of their works
  5. 5Electrical and Electronic Engineering6% of their works
  6. 6Education4% of their works

Research topics

Which keywords describe Tabitha Chukwudi Aghaunor's research?

The keywords of their largest research topics: Machine Learning, Deep Learning, Data Mining, Anomaly Detection, Feature Selection, Healthcare, IoT Security and Behavioral Analysis.

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. Machine Learning206 topics
  2. Deep Learning134 topics
  3. Data Mining92 topics
  4. Anomaly Detection72 topics
  5. Feature Selection72 topics
  6. Healthcare72 topics
  7. IoT Security72 topics
  8. Behavioral Analysis62 topics
  9. Big Data Analytics51 topic
  10. Medical Diagnosis51 topic
  11. Intrusion Detection41 topic
  12. Network Security41 topic
  13. Android Malware31 topic
  14. Detection31 topic
  15. Histopathology Images31 topic
  16. Medical Image Analysis31 topic
  17. Outlier Detection31 topic
  18. Phishing31 topic
  19. Spam Detection31 topic
  20. Unsupervised31 topic
  21. IoT21 topic
  22. Multi-label Learning21 topic
  23. Smart Cities21 topic
  24. Text Classification21 topic

Where does Tabitha Chukwudi Aghaunor work?

Tabitha Chukwudi Aghaunor's main affiliation in the publication record is Robert Morris University, United States.

How many publications and citations does Tabitha Chukwudi Aghaunor have?

OpenAlex counts 26 works and 64 citations for Tabitha Chukwudi Aghaunor, an h-index of 5, ranking #2,007,806 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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