Rachel Sparks
- Psychiatry and Mental health top 5%
- Epilepsy research and treatment 24
- Health Informatics top 5%
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- Radiomics and Machine Learning in Medical Imaging 8
- Advanced MRI Techniques and Applications 7
- Cognitive Neuroscience top 5%
- EEG and Brain-Computer Interfaces 16
- Neurology top 10%
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- Medical Image Segmentation Techniques 13
- Advanced Neural Network Applications 7
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- AI in cancer detection 11
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- Prostate Cancer Diagnosis and Treatment 6
- Co-authors
- Sébastien OurselinFernando Pérez‐GarcíaAnant MadabhushiJohn S. DuncanAnna MiserocchiAndrew W. McEvoyVejay N. VakhariaRoman Rodionov
- Journals
- SHILAP Revista de lepidopterología (1 paper)PLoS ONE (1 paper)Physical Review B (1 paper)
- Partner nations
- United KingdomUnited StatesChina
In The Last Decade
Rachel Sparks
70 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Psychiatry and Mental health 374
- Health Informatics 31
- Radiology, Nuclear Medicine and Imaging 428
- Cognitive Neuroscience 273
- Neurology 185
Countries citing papers authored by Rachel Sparks
This map shows the geographic impact of Rachel Sparks'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 Rachel Sparks with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rachel Sparks more than expected).
Fields of papers citing papers by Rachel Sparks
This network shows the impact of papers produced by Rachel Sparks. 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 Rachel Sparks. The network helps show where Rachel Sparks may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Rachel Sparks, 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 | 0 | |
| 3 | 2023 | 2 | |
| 4 | 2023 | 2 | |
| 5 | 2022 | 4 | |
| 6 | TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learningbreakdown → | 2021 | 283 |
| 7 | 2021 | 18 | |
| 8 | 2020 | 17 | |
| 9 | 2020 | 3 | |
| 10 | 2020 | 3 | |
| 11 | 2020 | 7 | |
| 12 | 2020 | 8 | |
| 13 | 2019 | 4 | |
| 14 | 2019 | 18 | |
| 15 | 2018 | 20 | |
| 16 | 2017 | 29 | |
| 17 | 2016 | 33 | |
| 18 | 2015 | 3 | |
| 19 | 2013 | 27 | |
| 20 | 2012 | 16 |
About Rachel Sparks
Rachel Sparks is a scholar working on Psychiatry and Mental health, Cognitive Neuroscience and Computer Vision and Pattern Recognition, having authored 75 papers that have together received 1.3k indexed citations. Recurring topics across this work include Epilepsy research and treatment (24 papers), EEG and Brain-Computer Interfaces (16 papers), Medical Image Segmentation Techniques (13 papers), AI in cancer detection (11 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), Advanced Neural Network Applications (7 papers), Advanced MRI Techniques and Applications (7 papers) and Prostate Cancer Diagnosis and Treatment (6 papers). The work is most often cited by research in Psychiatry and Mental health (374 citations), Health Informatics (31 citations) and Radiology, Nuclear Medicine and Imaging (428 citations). Rachel Sparks has collaborated with scholars based in United Kingdom, United States and China. Frequent co-authors include Sébastien Ourselin, Fernando Pérez‐García, Anant Madabhushi, John S. Duncan, Anna Miserocchi, Andrew W. McEvoy, Vejay N. Vakharia, Roman Rodionov, Aidan G. O’Keeffe and Sjoerd B. Vos. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Physical Review B.
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.