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Researcher · Bangladesh University · Bangladesh

Mohammed Ibrahim Hussain

Mohammed Ibrahim Hussain publishes mostly in Artificial Intelligence, Health Information Management and Electrical and Electronic Engineering, on topics such as Explainable Artificial Intelligence (XAI), Machine Learning in Healthcare and Artificial Intelligence in Healthcare.

OpenAlex
World rank
#1,078,952
of 7,710,434 ranked researchers
Rank in Bangladesh
#1,318
of 14,256
Works
36
Citations
122
Citations per work
3.4
h-index
6
i10-index 3Top 74% in Artificial Intelligence
Mohammed Ibrahim Hussain

What does Mohammed Ibrahim Hussain research?

Mohammed Ibrahim Hussain's work is mostly in Computer Science (32%), Health Professions (10%), Medicine (8%).

Everything else: 14 works · 39.9% of their workPhysical Sciences: 14 works · 38.6% of their workComputer Science: 11 works · 31.8% of their workArtificial Intelligence: 11 works · 31.8% of their workEngineering: 2 works · 6.8% of their workElectrical and Electronic Engineering: 2 works · 6.8% of their workHealth Sciences: 7 works · 18.1% of their workHealth Professions: 4 works · 10.2% of their workHealth Information Management: 4 works · 10.2% of their workMedicine: 3 works · 7.9% of their workRadiology, Nuclear Medicine and Imaging: 2 works · 4.5% of their workPulmonary and Respiratory Medicine: 1 works · 3.4% of their workLife Sciences: 1 works · 3.4% of their workNeuroscience: 1 works · 3.4% of their workNeurology: 1 works · 3.4% of their workTHEIR WORKMohammed IbrahimHussain36works
Life Sciences3%Physical Sciences39%Health Sciences18%

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. Everything else1439.9%
    1. Computer Science1131.8%
    2. Engineering26.8%
    1. Health Professions410.2%
    2. Medicine37.9%
    1. Neuroscience13.4%
  1. 1Artificial Intelligence32% of their works
  2. 2Health Information Management10% of their works
  3. 3Electrical and Electronic Engineering7% of their works
  4. 4Radiology, Nuclear Medicine and Imaging4% of their works
  5. 5Neurology3% of their works
  6. 6Pulmonary and Respiratory Medicine3% of their works

Research topics

Which keywords describe Mohammed Ibrahim Hussain's research?

The keywords of their largest research topics: Healthcare, Machine Learning, Deep Learning, Data Mining, Electronic Health Records, Interpretable Models, Machine Learning Interpretability and Predictive Modeling.

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 20 words, with their numbers
  1. Healthcare192 topics
  2. Machine Learning174 topics
  3. Deep Learning163 topics
  4. Data Mining112 topics
  5. Electronic Health Records101 topic
  6. Interpretable Models101 topic
  7. Machine Learning Interpretability101 topic
  8. Predictive Modeling101 topic
  9. Big Data Analytics91 topic
  10. Medical Diagnosis91 topic
  11. Brain Tumor31 topic
  12. Histopathology Images31 topic
  13. MRI31 topic
  14. Medical Image Analysis31 topic
  15. Agriculture21 topic
  16. CT Screening21 topic
  17. Differential Privacy21 topic
  18. Federated Learning21 topic
  19. Lung Cancer21 topic
  20. Water Management21 topic

Where does Mohammed Ibrahim Hussain work?

Mohammed Ibrahim Hussain's main affiliation in the publication record is Bangladesh University, Bangladesh.

How many publications and citations does Mohammed Ibrahim Hussain have?

OpenAlex counts 36 works and 122 citations for Mohammed Ibrahim Hussain, an h-index of 6, ranking #1,078,952 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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