Ahmed Abdulkadir
- Cognitive Neuroscience top 5%
- Functional Brain Connectivity Studies 15
- Psychiatry and Mental health top 5%
- Dementia and Cognitive Impairment Research 16
- Neurology top 5%
- Brain Tumor Detection and Classification 5
- Health Informatics top 5%
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- Advanced Neuroimaging Techniques and Applications 7
- Radiomics and Machine Learning in Medical Imaging 5
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- Alzheimer's disease research and treatments 7
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- Genetic Neurodegenerative Diseases 6
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- Machine Learning in Healthcare 4
- Co-authors
- Stefan KlöppelClifford R. JackPrashanthi VemuriJessica PeterJanaı́na Mourão-MirandaNikolaos KoutsoulerisGunnar KruegerCristina Granziera
- Partner nations
- SwitzerlandGermanyUnited States
In The Last Decade
Ahmed Abdulkadir
48 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 122
- Cognitive Neuroscience 592
- Psychiatry and Mental health 416
- Neurology 215
- Health Informatics 33
- Radiology, Nuclear Medicine and Imaging 422
Countries citing papers authored by Ahmed Abdulkadir
This map shows the geographic impact of Ahmed Abdulkadir'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 Ahmed Abdulkadir with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ahmed Abdulkadir more than expected).
Fields of papers citing papers by Ahmed Abdulkadir
This network shows the impact of papers produced by Ahmed Abdulkadir. 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 Ahmed Abdulkadir. The network helps show where Ahmed Abdulkadir may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ahmed Abdulkadir, 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 | 2024 | 2 | |
| 3 | A Comprehensive Survey of Deep Transfer Learning for Anomaly Detection in Industrial Time Series: Methods, Applications, and Directionsbreakdown → | 2024 | 70 |
| 4 | 2023 | 1 | |
| 5 | 2022 | 0 | |
| 6 | 2022 | 2 | |
| 7 | 2022 | 12 | |
| 8 | 2022 | 0 | |
| 9 | 2021 | 18 | |
| 10 | 2020 | 18 | |
| 11 | 2019 | 4 | |
| 12 | 2018 | 3 | |
| 13 | 2017 | 24 | |
| 14 | 2015 | 50 | |
| 15 | Voxel-based multi-class classification of AD, MCI, and elderly controls | 2014 | 4 |
| 16 | 2014 | 27 | |
| 17 | 2014 | 154 | |
| 18 | 2013 | 22 | |
| 19 | 2011 | 67 | |
| 20 | 2011 | 219 |
About Ahmed Abdulkadir
Ahmed Abdulkadir is a scholar working on Health Informatics, Psychiatry and Mental health and Neurology, having authored 52 papers that have together received 1.4k indexed citations. Recurring topics across this work include Dementia and Cognitive Impairment Research (16 papers), Functional Brain Connectivity Studies (15 papers), Alzheimer's disease research and treatments (7 papers), Advanced Neuroimaging Techniques and Applications (7 papers), Genetic Neurodegenerative Diseases (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Brain Tumor Detection and Classification (5 papers) and Machine Learning in Healthcare (4 papers). The work is most often cited by research in Cognitive Neuroscience (592 citations), Psychiatry and Mental health (416 citations) and Neurology (215 citations). Ahmed Abdulkadir has collaborated with scholars based in Switzerland, Germany and United States. Frequent co-authors include Stefan Klöppel, Clifford R. Jack, Prashanthi Vemuri, Jessica Peter, Janaı́na Mourão-Miranda, Nikolaos Koutsouleris, Gunnar Krueger, Cristina Granziera, Meritxell Bach Cuadra and Christoph Nissen. Their work appears in journals such as NeuroImage, Scientific Reports and Brain Research.
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.