Jeremy Lynch
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education 3
- Neurology top 10%
- Intracranial Aneurysms: Treatment and Complications 10
- Vascular Malformations Diagnosis and Treatment 7
- Traumatic Brain Injury and Neurovascular Disturbances 6
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- Cerebrovascular and Carotid Artery Diseases 6
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- Acute Ischemic Stroke Management 5
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- Radiomics and Machine Learning in Medical Imaging 4
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- Machine Learning in Healthcare 2
- Co-authors
- T. M. HammondAjay BelgaumkarThomas C. BoothIndran DavagnanamSébastien OurselinMatthew TownendJames H. ColeAsif Mazumder
- Cited by
- Health InformaticsNeurologySurgery
- Journals
- Journal of NeuroInterventional Surgery (5 papers)Clinical Neuroradiology (4 papers)European Radiology (2 papers)
- Partner nations
- United KingdomCanadaTürkiye
In The Last Decade
Jeremy Lynch
26 papers receiving 529 citations
Peers
Comparison fields: 5 of 93
- Health Informatics 30
- Neurology 147
- Surgery 182
- Pharmacy 18
- Pulmonary and Respiratory Medicine 118
Countries citing papers authored by Jeremy Lynch
This map shows the geographic impact of Jeremy Lynch'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 Jeremy Lynch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeremy Lynch more than expected).
Fields of papers citing papers by Jeremy Lynch
This network shows the impact of papers produced by Jeremy Lynch. 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 Jeremy Lynch. The network helps show where Jeremy Lynch may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jeremy Lynch, 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 | 1 | |
| 2 | 2024 | 8 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 9 | |
| 5 | 2023 | 5 | |
| 6 | 2023 | 1 | |
| 7 | 2023 | 11 | |
| 8 | 2022 | 61 | |
| 9 | 2022 | 19 | |
| 10 | 2021 | 19 | |
| 11 | 2021 | 6 | |
| 12 | 2021 | 30 | |
| 13 | 2021 | 37 | |
| 14 | 2020 | 11 | |
| 15 | 2019 | 27 | |
| 16 | 2014 | 1 | |
| 17 | 2012 | 1 | |
| 18 | 2012 | 71 | |
| 19 | 2010 | 118 | |
| 20 | [Pyomucocele of the sphenoid sinus with thrombosis of the cavernous sinuses and its ocular complications]. | 1972 | 1 |
About Jeremy Lynch
Jeremy Lynch is a scholar working on Health Informatics, Neurology and Internal Medicine, having authored 27 papers that have together received 542 indexed citations. Recurring topics across this work include Intracranial Aneurysms: Treatment and Complications (10 papers), Vascular Malformations Diagnosis and Treatment (7 papers), Cerebrovascular and Carotid Artery Diseases (6 papers), Traumatic Brain Injury and Neurovascular Disturbances (6 papers), Acute Ischemic Stroke Management (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Machine Learning in Healthcare (2 papers). The work is most often cited by research in Health Informatics (30 citations), Neurology (147 citations) and Surgery (182 citations). Jeremy Lynch has collaborated with scholars based in United Kingdom, Canada and Türkiye. Frequent co-authors include T. M. Hammond, Ajay Belgaumkar, Thomas C. Booth, Indran Davagnanam, Sébastien Ourselin, Matthew Townend, James H. Cole, Asif Mazumder, Gareth J. Barker and David Wood. Their work appears in journals such as Journal of NeuroInterventional Surgery, Clinical Neuroradiology, European Radiology, Journal of surgical education and International Journal of Surgery.
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.