Asmaa Hammad

518 citations
8 papers · 274 · 1 hit paper · h-index 5

Impact in

Papers in

Asmaa Hammad

7 papers receiving 265 citations

Asmaa Hammad's Hit Papers

Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review 2022 · 206 citations
2060+1+2Years since publication50100150200

Peers

Asmaa Hammad
Comparison fields: 5 of 76
  • Experimental and Cognitive Psychology 127
  • Cognitive Neuroscience 155
  • Human-Computer Interaction 28
  • Cardiology and Cardiovascular Medicine 31
  • Computer Vision and Pattern Recognition 26
Replace Pallavi Pandey with:
Pallavi Pandey India
Qiuhao Zeng Singapore
Yuzhe Zhang China
Omar AlZoubi Jordan
Henry Candra Indonesia
Muhammad Adeel Asghar Pakistan
Hongli Chang China
Jinjing Song China
Asmaa Hammad relative to Pallavi Pandey India Pallavi Pandey's profile →
Citations per field
00.5×2.7×
Pallavi Pandey · 1×
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 14 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

8 of 8 papers shown
#Work
1
Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review
Hit paper breakdown →
2022206
2 202428
3 201917
4 20239
5 20249
6 20223
7 20182
8 20180

About Asmaa Hammad

Asmaa Hammad is a scholar working on Molecular Biology, Cognitive Neuroscience, Experimental and Cognitive Psychology, Pathology and Forensic Medicine and Oncology, having authored 8 papers that have together received 274 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (3 papers), Emotion and Mood Recognition (3 papers), Cancer Treatment and Pharmacology (2 papers), Heme Oxygenase-1 and Carbon Monoxide (2 papers), Gaze Tracking and Assistive Technology (1 paper), ECG Monitoring and Analysis (1 paper), Pain Mechanisms and Treatments (1 paper) and Alcohol Consumption and Health Effects (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (127 citations), Cognitive Neuroscience (155 citations), Human-Computer Interaction (28 citations), Cardiology and Cardiovascular Medicine (31 citations) and Computer Vision and Pattern Recognition (26 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, Ashraf Taye, Al‐Shaimaa F. Ahmed, Gehan H. Heeba, Sara Mohamed Naguib Abdel Hafez, Mohamed M. Sayed‐Ahmed, Mahmoud El‐Daly and Nagwan Abdel Samee. Their work appears in journals such as Computers in Biology and Medicine, Chemico-Biological Interactions, Life Sciences, Neural Computing and Applications and Cluster Computing.

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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