Science Explorer Back to mapMap
Discussion
Researcher · Menoufia University · Egypt

Mohamed Adel Hammad

Mohamed Adel Hammad publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Cardiology and Cardiovascular Medicine, on topics such as ECG Monitoring and Analysis, EEG and Brain-Computer Interfaces and COVID-19 diagnosis using AI.

ORCID 0000-0002-6506-3083 OpenAlex
World rank
#40,694
of 7,710,434 ranked researchers
Rank in Egypt
#105
of 36,277
Works
128
Citations
4.8k
Citations per work
37.9
h-index
37
i10-index 59Top 2.7% in Artificial Intelligence
Mohamed Adel Hammad

What does Mohamed Adel Hammad research?

Mohamed Adel Hammad's work is mostly in Computer Science (30%), Medicine (15%), Neuroscience (6%).

Everything else: 62 works · 48.7% of their workPhysical Sciences: 39 works · 30.4% of their workComputer Science: 39 works · 30.4% of their workArtificial Intelligence: 17 works · 13.0% of their workComputer Vision and Pattern Recognition: 14 works · 10.6% of their workInformation Systems: 9 works · 6.8% of their workHealth Sciences: 20 works · 15.3% of their workMedicine: 20 works · 15.3% of their workCardiology and Cardiovascular Medicine: 11 works · 8.8% of their workRadiology, Nuclear Medicine and Imaging: 8 works · 6.5% of their workLife Sciences: 7 works · 5.6% of their workNeuroscience: 7 works · 5.6% of their workCognitive Neuroscience: 7 works · 5.6% of their workTHEIR WORKMohamed AdelHammad128works
Life Sciences6%Physical Sciences30%Health 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. Everything else6248.7%
    1. Computer Science3930.4%
    1. Medicine2015.3%
    1. Neuroscience75.6%
  1. 1Artificial Intelligence13% of their works
  2. 2Computer Vision and Pattern Recognition11% of their works
  3. 3Cardiology and Cardiovascular Medicine9% of their works
  4. 4Information Systems7% of their works
  5. 5Radiology, Nuclear Medicine and Imaging6% of their works
  6. 6Cognitive Neuroscience6% of their works

Research topics

Which keywords describe Mohamed Adel Hammad's research?

The keywords of their largest research topics: Deep Learning, Arrhythmia Detection, ECG Signal, Convolutional Neural Networks, Authentication, Brain-Computer Interfaces, EEG Analysis and Security.

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 20 words, with their numbers
  1. Deep Learning554 topics
  2. Arrhythmia Detection251 topic
  3. ECG Signal251 topic
  4. Convolutional Neural Networks232 topics
  5. Authentication192 topics
  6. Brain-Computer Interfaces191 topic
  7. EEG Analysis191 topic
  8. Security192 topics
  9. COVID-19151 topic
  10. Medical Imaging151 topic
  11. Biometric Recognition111 topic
  12. Privacy111 topic
  13. Biometrics81 topic
  14. Image Recognition81 topic
  15. Object Detection81 topic
  16. Passwords81 topic
  17. Photoplethysmography81 topic
  18. Remote Monitoring81 topic
  19. Anomaly Detection71 topic
  20. Unsupervised71 topic

Where does Mohamed Adel Hammad work?

Mohamed Adel Hammad's main affiliation in the publication record is Menoufia University, Egypt.

How many publications and citations does Mohamed Adel Hammad have?

OpenAlex counts 128 works and 4,847 citations for Mohamed Adel Hammad, an h-index of 37, ranking #40,694 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.

Discussion

Ask a question or share a note about Mohamed Adel Hammad. Posts are plain text and can be reported.