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Researcher · Université de ain Témouchent · Algeria

Mohammed Lamine Benomar

Mohammed Lamine Benomar publishes mostly in Computer Vision and Pattern Recognition, Artificial Intelligence 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 0000-0001-8982-9760 OpenAlex
World rank
#5,231,130
of 7,710,434 ranked researchers
Rank in Algeria
#4,404
of 10,068
Works
19
Citations
80
Citations per work
4.2
h-index
4
i10-index 3Top 94% in Computer Vision and Pattern Recognition
Mohammed Lamine Benomar

What does Mohammed Lamine Benomar research?

Mohammed Lamine Benomar's work is mostly in Computer Science (53%), Medicine (28%), Biochemistry, Genetics and Molecular Biology (6%).

Physical Sciences: 10 works · 53.2% of their workComputer Science: 10 works · 53.2% of their workComputer Vision and Pattern Recognition: 5 works · 27.7% of their workArtificial Intelligence: 5 works · 25.5% of their workHealth Sciences: 5 works · 27.7% of their workMedicine: 5 works · 27.7% of their workRadiology, Nuclear Medicine and Imaging: 3 works · 14.9% of their workCardiology and Cardiovascular Medicine: 1 works · 6.4% of their workPulmonary and Respiratory Medicine: 1 works · 6.4% of their workEverything else: 2 works · 12.7% of their workLife Sciences: 1 works · 6.4% of their workBiochemistry, Genetics and Molecular Biology: 1 works · 6.4% of their workBiophysics: 1 works · 6.4% of their workTHEIR WORKMohammed LamineBenomar19works
Life Sciences6%Physical Sciences53%Health Sciences28%

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 Science1053.2%
    1. Medicine527.7%
  3. Everything else212.7%
    1. Biochemistry, Genetics and Molecular Biology16.4%
  1. 1Computer Vision and Pattern Recognition28% of their works
  2. 2Artificial Intelligence26% of their works
  3. 3Radiology, Nuclear Medicine and Imaging15% of their works
  4. 4Pulmonary and Respiratory Medicine6% of their works
  5. 5Biophysics6% of their works
  6. 6Cardiology and Cardiovascular Medicine6% of their works

Research topics

Which keywords describe Mohammed Lamine Benomar's research?

The keywords of their largest research topics: Machine Learning, Convolutional Neural Networks, Medical Image Analysis, Deep Learning, 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.

All 24 words, with their numbers
  1. Machine Learning285 topics
  2. Convolutional Neural Networks192 topics
  3. Medical Image Analysis192 topics
  4. Deep Learning185 topics
  5. Feature Extraction143 topics
  6. Computer-Aided Detection111 topic
  7. Histopathology Images111 topic
  8. Image Processing112 topics
  9. Leukemia Classification81 topic
  10. Malaria Parasite Detection81 topic
  11. Medical Imaging62 topics
  12. Predictive Modeling62 topics
  13. Quantitative Analysis51 topic
  14. Radiomics51 topic
  15. Bioimage Analysis31 topic
  16. High-Content Screening31 topic
  17. Colorectal Cancer21 topic
  18. Diabetic Retinopathy21 topic
  19. Retinal Disease21 topic
  20. Screening21 topic
  21. Brain Tumor11 topic
  22. Electronic Health Records11 topic
  23. Healthcare11 topic
  24. MRI11 topic

Where does Mohammed Lamine Benomar work?

Mohammed Lamine Benomar's main affiliation in the publication record is Université de ain Témouchent, Algeria.

How many publications and citations does Mohammed Lamine Benomar have?

OpenAlex counts 19 works and 80 citations for Mohammed Lamine Benomar, an h-index of 4, ranking #5,231,130 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.

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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