Mohamed Hammad

75 papers receiving 2.8k citations

Mohamed Hammad's Hit Papers

Two-tier deep and machine learning approach optimized by adaptive multi-population firefly algorithm for software defects prediction 2025 · 27 citations
270+2+4Years since publication100200300

Peers

Mohamed Hammad
Comparison fields: 5 of 153
  • Health Informatics 56
  • Cardiology and Cardiovascular Medicine 750
  • Signal Processing 374
  • Health Information Management 139
  • Cognitive Neuroscience 568
Replace Paweł Pławiak with:
Paweł Pławiak Poland
Siti Nurmaini Indonesia
Damodar Reddy Edla India
Mirjam Jonkman Australia
Zafer Cömert Türkiye
Friso De Boer Australia
Charence Wong United Kingdom
İbrahim Türkoğlu Türkiye
Narendra D. Londhe India
Adi Alhudhaif Saudi Arabia
Mohamed Hammad relative to Paweł Pławiak Poland Paweł Pławiak's profile →
Citations per field
00.5×1.5×
Paweł Pławiak · 1×
Citations per year

Countries citing papers authored by Mohamed Hammad

Since Specialization
Citations

This map shows the geographic impact of Mohamed 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 Mohamed Hammad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohamed Hammad more than expected).

Fields of papers citing papers by Mohamed Hammad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohamed 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 Mohamed Hammad. The network helps show where Mohamed Hammad may publish in the future.

Co-authors

The 25 scholars most cited alongside Mohamed 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 Mohamed Hammad Line = papers co-authored together Mohamed Hammad links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Progress in Outlier Detection Techniques: A Survey
Hit paper breakdown →
2019343
2 2020186
3 2018177
4 2018153
5 2020146
6 2021144
7 2020142
8 2021111
9 202098
10 202396
11 201995
12 201879
13 202274
14 202366
15 202264
16 201858
17 202353
18 201852
19 202247
20 202145

About Mohamed Hammad

Mohamed Hammad is a scholar working on Cardiology and Cardiovascular Medicine, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Artificial Intelligence and Signal Processing, having authored 82 papers that have together received 2.9k indexed citations. Recurring topics across this work include ECG Monitoring and Analysis (21 papers), EEG and Brain-Computer Interfaces (18 papers), Biometric Identification and Security (9 papers), COVID-19 diagnosis using AI (9 papers), Anomaly Detection Techniques and Applications (7 papers), Non-Invasive Vital Sign Monitoring (7 papers), Advanced Neural Network Applications (7 papers) and User Authentication and Security Systems (6 papers). The work is most often cited by research in Health Informatics (56 citations), Cardiology and Cardiovascular Medicine (750 citations), Signal Processing (374 citations), Health Information Management (139 citations) and Cognitive Neuroscience (568 citations). Mohamed Hammad has collaborated with scholars based in Egypt, Saudi Arabia and Poland. Frequent co-authors include Kuanquan Wang, Ahmed A. Abd El‐Latif, Paweł Pławiak, Mohamed Jaward Bah, Hongzhi Wang, Abdullah M. Iliyasu, Brij B. Gupta, Ryszard Tadeusiewicz, Ahmed Sedik and Yashu Liu. Their work appears in journals such as IEEE Access, Sensors, Journal of Applied Biomedicine, Information Sciences and Applied Sciences.

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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