Asmaa Hammad

550 citations
9 papers · 305 · 1 hit paper · h-index 5

Impact in

Papers in

Asmaa Hammad

7 papers receiving 298 citations

Asmaa Hammad's Hit Papers

Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review 2022 · 230 citations
2300+1+2Years since publication50100150200

Peers

Asmaa Hammad
Comparison fields: 5 of 74
  • Experimental and Cognitive Psychology 140
  • Cognitive Neuroscience 160
  • Human-Computer Interaction 26
  • Geriatrics and Gerontology 5
  • Cardiology and Cardiovascular Medicine 30
Replace Gabriela Moise with:
Gabriela Moise Romania
Omar AlZoubi Jordan
Yuzhe Zhang China
Ruoyu Du China
Qiuhao Zeng Singapore
Henry Candra Indonesia
Xiaoye Huang China
Muhammad Adeel Asghar Pakistan
Pallavi Pandey India
Hongli Chang China
Asmaa Hammad relative to Gabriela Moise Romania Gabriela Moise's profile →
Citations per field
00.5×1.5×2.3×
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Citations per year

Countries citing papers authored by Asmaa Hammad

Since Specialization
Citations

This map shows the geographic impact of Asmaa Hammad's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Asmaa Hammad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Asmaa Hammad more than expected).

Fields of papers citing papers by Asmaa Hammad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Asmaa Hammad. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Asmaa Hammad. The network helps show where Asmaa Hammad may publish in the future.

Co-authors

The 16 scholars most cited alongside Asmaa Hammad, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Asmaa Hammad Line = papers co-authored together Asmaa Hammad links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review
Hit paper breakdown →
2022230
2 202430
3 201917
4 202413
5 20239
6 20224
7 20182
8 20180
9 20260

About Asmaa Hammad

Asmaa Hammad is a scholar working on Cognitive Neuroscience, Molecular Biology, Experimental and Cognitive Psychology, Pathology and Forensic Medicine and Oncology, having authored 9 papers that have together received 305 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (4 papers), Emotion and Mood Recognition (3 papers), Cancer Treatment and Pharmacology (2 papers), Heme Oxygenase-1 and Carbon Monoxide (2 papers), Multiple Myeloma Research and Treatments (1 paper), Silymarin and Mushroom Poisoning (1 paper), Genomics and Phylogenetic Studies (1 paper) and Advanced Glycation End Products research (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (140 citations), Cognitive Neuroscience (160 citations), Human-Computer Interaction (26 citations), Geriatrics and Gerontology (5 citations) and Cardiology and Cardiovascular Medicine (30 citations). Asmaa Hammad has collaborated with scholars based in Egypt and Saudi Arabia. Frequent co-authors include Abdelmgeid A. Ali, Essam H. Houssein, Marwa M. Emam, Al‐Shaimaa F. Ahmed, Ashraf Taye, Gehan H. Heeba, Mahmoud El‐Daly, Nagwan Abdel Samee, Manal Abdullah Alohali and Mohamed Mansour Khalifa. Their work appears in journals such as Biomedical Signal Processing and Control, Life Sciences, Neural Computing and Applications, Computers in Biology and Medicine and Chemico-Biological Interactions.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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