Laith Alzubaidi
- Health Informatics top 0.2%
- Artificial Intelligence in Healthcare and Education 5
- Artificial Intelligence top 0.5%
- Anomaly Detection Techniques and Applications 13
- AI in cancer detection 13
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- Digital Imaging for Blood Diseases 4
- Health Information Management top 0.5%
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- COVID-19 diagnosis using AI 15
- Radiomics and Machine Learning in Medical Imaging 9
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- Network Security and Intrusion Detection 6
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- Model Reduction and Neural Networks 5
- Co-authors
- Mohammed A. FadhelJinglan ZhangYe DuanOmran Al-ShammaJosé SantamaríaLaith FarhanAmjad J. HumaidiMuthana Al‐Amidie
- Partner nations
- AustraliaIraqUnited States
In The Last Decade
Laith Alzubaidi
73 papers receiving 7.2k citations
Hit Papers
Peers
Comparison fields: 5 of 213
- Health Informatics 290
- Artificial Intelligence 2.2k
- Computer Vision and Pattern Recognition 1.4k
- Health Information Management 244
- Radiology, Nuclear Medicine and Imaging 1.2k
Countries citing papers authored by Laith Alzubaidi
This map shows the geographic impact of Laith Alzubaidi'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 Laith Alzubaidi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laith Alzubaidi more than expected).
Fields of papers citing papers by Laith Alzubaidi
This network shows the impact of papers produced by Laith Alzubaidi. 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 Laith Alzubaidi. The network helps show where Laith Alzubaidi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Laith Alzubaidi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 6 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 2 | |
| 5 | 2025 | 1 | |
| 6 | 2024 | 11 | |
| 7 | 2024 | 10 | |
| 8 | A systematic review of trustworthy artificial intelligence applications in natural disastersbreakdown → | 2024 | 78 |
| 9 | 2024 | 28 | |
| 10 | 2024 | 20 | |
| 11 | 2024 | 19 | |
| 12 | 2023 | 28 | |
| 13 | 2023 | 15 | |
| 14 | A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusionbreakdown → | 2023 | 372 |
| 15 | 2023 | 4 | |
| 16 | 2023 | 27 | |
| 17 | 2023 | 22 | |
| 18 | 2021 | 13 | |
| 19 | 2020 | 123 | |
| 20 | 2020 | 104 |
About Laith Alzubaidi
Laith Alzubaidi is a scholar working on Health Informatics, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 83 papers that have together received 7.4k indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (15 papers), Anomaly Detection Techniques and Applications (13 papers), AI in cancer detection (13 papers), Radiomics and Machine Learning in Medical Imaging (9 papers), Network Security and Intrusion Detection (6 papers), Model Reduction and Neural Networks (5 papers), Artificial Intelligence in Healthcare and Education (5 papers) and Digital Imaging for Blood Diseases (4 papers). The work is most often cited by research in Health Informatics (290 citations), Artificial Intelligence (2.2k citations) and Computer Vision and Pattern Recognition (1.4k citations). Laith Alzubaidi has collaborated with scholars based in Australia, Iraq and United States. Frequent co-authors include Mohammed A. Fadhel, Jinglan Zhang, Ye Duan, Omran Al-Shamma, José Santamaría, Laith Farhan, Amjad J. Humaidi, Muthana Al‐Amidie, Ayad Q. Al-Dujaili and Yuantong Gu. Their work appears in journals such as Electronics, Sensors, Information Fusion, Intelligent Systems with Applications and Engineering Applications of Artificial Intelligence.
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.