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Researcher · Federal University Wukari · ??

Moshood Abiola Hambali

Moshood Abiola Hambali publishes mostly in Artificial Intelligence, Marketing and Computer Vision and Pattern Recognition, on topics such as Customer churn and segmentation, Gene expression and cancer classification and Machine Learning in Bioinformatics.

ORCID 0000-0002-2194-9376 OpenAlex
World rank
#3,407,663
of 7,710,434 ranked researchers
Rank in ??
#5,988
of 21,892
Works
23
Citations
257
Citations per work
11.2
h-index
9
i10-index 6Top 49% in Artificial Intelligence
Moshood Abiola Hambali

What does Moshood Abiola Hambali research?

Moshood Abiola Hambali's work is mostly in Computer Science (48%), Business, Management and Accounting (15%), Biochemistry, Genetics and Molecular Biology (7%).

Physical Sciences: 11 works · 48.2% of their workComputer Science: 11 works · 48.2% of their workArtificial Intelligence: 4 works · 18.5% of their workComputer Vision and Pattern Recognition: 3 works · 13.0% of their workInformation Systems: 2 works · 9.3% of their workSignal Processing: 2 works · 7.4% of their workEverything else: 7 works · 29.6% of their workSocial Sciences: 3 works · 14.8% of their workBusiness, Management and Accounting: 3 works · 14.8% of their workMarketing: 3 works · 14.8% of their workLife Sciences: 2 works · 7.4% of their workBiochemistry, Genetics and Molecular Biology: 2 works · 7.4% of their workMolecular Biology: 2 works · 7.4% of their workTHEIR WORKMoshood AbiolaHambali23works
Life Sciences7%Physical Sciences48%Social Sciences15%

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 Science1148.2%
  2. Everything else729.6%
    1. Business, Management and Accounting314.8%
    1. Biochemistry, Genetics and Molecular Biology27.4%
  1. 1Artificial Intelligence18% of their works
  2. 2Marketing15% of their works
  3. 3Computer Vision and Pattern Recognition13% of their works
  4. 4Information Systems9% of their works
  5. 5Signal Processing7% of their works
  6. 6Molecular Biology7% of their works

Research topics

Which keywords describe Moshood Abiola Hambali's research?

The keywords of their largest research topics: Machine Learning, Data Mining, Deep Learning, Churn Prediction, Customer Equity, Bioinformatics, Feature Selection and Classification.

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 21 words, with their numbers
  1. Machine Learning156 topics
  2. Data Mining72 topics
  3. Deep Learning63 topics
  4. Churn Prediction51 topic
  5. Customer Equity51 topic
  6. Bioinformatics42 topics
  7. Feature Selection42 topics
  8. Classification21 topic
  9. Gene Expression21 topic
  10. Histopathology Images21 topic
  11. Imbalanced Data21 topic
  12. Intrusion Detection21 topic
  13. Medical Image Analysis21 topic
  14. Microarray21 topic
  15. Multi-label Learning21 topic
  16. Network Security21 topic
  17. Opinion Mining21 topic
  18. Protein21 topic
  19. Sentiment Analysis21 topic
  20. Subcellular Localization21 topic
  21. Text Classification21 topic

Where does Moshood Abiola Hambali work?

Moshood Abiola Hambali's main affiliation in the publication record is Federal University Wukari, ??.

How many publications and citations does Moshood Abiola Hambali have?

OpenAlex counts 23 works and 257 citations for Moshood Abiola Hambali, an h-index of 9, ranking #3,407,663 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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