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Researcher · Multimedia University · Malaysia

Zaka Ur Rehman

Zaka Ur Rehman publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, on topics such as AI in cancer detection, Digital Imaging for Blood Diseases and Radiomics and Machine Learning in Medical Imaging.

ORCID 0000-0003-1341-6366 OpenAlex
World rank
#1,291,086
of 7,710,434 ranked researchers
Rank in Malaysia
#4,699
of 41,196
Works
42
Citations
795
Citations per work
18.9
h-index
9
i10-index 9Top 49% in Artificial Intelligence
Zaka Ur Rehman

What does Zaka Ur Rehman research?

Zaka Ur Rehman's work is mostly in Computer Science (38%), Medicine (19%), Biochemistry, Genetics and Molecular Biology (5%).

Physical Sciences: 16 works · 37.5% of their workComputer Science: 16 works · 37.5% of their workArtificial Intelligence: 9 works · 21.4% of their workComputer Vision and Pattern Recognition: 7 works · 16.1% of their workEverything else: 14 works · 32.9% of their workHealth Sciences: 8 works · 18.8% of their workMedicine: 8 works · 18.8% of their workRadiology, Nuclear Medicine and Imaging: 6 works · 14.3% of their workOncology: 2 works · 4.5% of their workLife Sciences: 5 works · 10.8% of their workBiochemistry, Genetics and Molecular Biology: 2 works · 5.4% of their workBiophysics: 2 works · 5.4% of their workNeuroscience: 2 works · 5.4% of their workNeurology: 2 works · 5.4% of their workTHEIR WORKZaka Ur Rehman42works
Life Sciences11%Physical Sciences38%Health Sciences19%

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 Science1637.5%
  2. Everything else1432.9%
    1. Medicine818.8%
    1. Biochemistry, Genetics and Molecular Biology25.4%
    2. Neuroscience25.4%
  1. 1Artificial Intelligence21% of their works
  2. 2Computer Vision and Pattern Recognition16% of their works
  3. 3Radiology, Nuclear Medicine and Imaging14% of their works
  4. 4Biophysics5% of their works
  5. 5Neurology5% of their works
  6. 6Oncology4% of their works

Research topics

Which keywords describe Zaka Ur Rehman's research?

The keywords of their largest research topics: Machine Learning, Deep Learning, Convolutional Neural Networks, Medical Image Analysis, Feature Extraction, Computer-Aided Detection, Histopathology Images and Image Processing.

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 25 words, with their numbers
  1. Machine Learning445 topics
  2. Deep Learning375 topics
  3. Convolutional Neural Networks293 topics
  4. Medical Image Analysis283 topics
  5. Feature Extraction203 topics
  6. Computer-Aided Detection181 topic
  7. Histopathology Images181 topic
  8. Image Processing132 topics
  9. Medical Imaging132 topics
  10. Texture Analysis102 topics
  11. Image Segmentation92 topics
  12. Leukemia Classification71 topic
  13. Malaria Parasite Detection71 topic
  14. Quantitative Analysis71 topic
  15. Radiomics71 topic
  16. Bioimage Analysis61 topic
  17. Brain Tumor61 topic
  18. High-Content Screening61 topic
  19. MRI61 topic
  20. Breast Cancer41 topic
  21. HER241 topic
  22. Image Recognition41 topic
  23. Object Detection41 topic
  24. Active Contours31 topic
  25. Graph Cuts31 topic

Where does Zaka Ur Rehman work?

Zaka Ur Rehman's main affiliation in the publication record is Multimedia University, Malaysia.

How many publications and citations does Zaka Ur Rehman have?

OpenAlex counts 42 works and 795 citations for Zaka Ur Rehman, an h-index of 9, ranking #1,291,086 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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