James H. Cole

16.9k total citations · 4 hit papers
159 papers, 6.4k citations indexed

About

James H. Cole is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Psychiatry and Mental health. According to data from OpenAlex, James H. Cole has authored 159 papers receiving a total of 6.4k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Cognitive Neuroscience, 43 papers in Radiology, Nuclear Medicine and Imaging and 36 papers in Psychiatry and Mental health. Recurrent topics in James H. Cole's work include Functional Brain Connectivity Studies (40 papers), Advanced Neuroimaging Techniques and Applications (35 papers) and Dementia and Cognitive Impairment Research (26 papers). James H. Cole is often cited by papers focused on Functional Brain Connectivity Studies (40 papers), Advanced Neuroimaging Techniques and Applications (35 papers) and Dementia and Cognitive Impairment Research (26 papers). James H. Cole collaborates with scholars based in United Kingdom, United States and Netherlands. James H. Cole's co-authors include Katja Franke, David Sharp, Robert Leech, Cynthia H.Y. Fu, Riccardo E. Marioni, Ian J. Deary, Matthan W.A. Caan, Sarah E. Harris, Peter McGuffin and Claire J. Steves and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and The Journal of Immunology.

In The Last Decade

James H. Cole

150 papers receiving 6.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker

2017 523 citations James H. Cole, Matthan W.A. Caan et al. profile →
Predicting Age Using Neuroimaging: Innovative Brain Ageing Biomarkers

2017 519 citations James H. Cole, Katja Franke profile →
Brain age predicts mortality

2017 486 citations James H. Cole, Stuart J. Ritchie et al. profile →
Prediction of brain age suggests accelerated atrophy after traumatic brain injury

2015 317 citations James H. Cole, Robert Leech et al. profile →

Peers

James H. Cole

RNMI

PMH

NEURO

Simon R. Cox United Kingdom

Janie Corley United Kingdom

Nicola Toschi Italy

Anderson M. Winkler United States

Lei Wang United States

Arne Møller Denmark

Jie Lu China

Richard Camicioli Canada

Owen Carmichael United States

André F. Marquand United Kingdom

Simon R. Cox United Kingdom

James H. Cole

1.8k ×0.8

1.3k ×0.9

RNMI

977 ×0.8

PMH

275 ×0.3

NEURO

974 ×1.1

Citations per year, relative to James H. Cole James H. Cole (= 1×) peers Simon R. Cox

Countries citing papers authored by James H. Cole

Since Specialization

Citations

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

Fields of papers citing papers by James H. Cole

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James H. Cole. 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 James H. Cole. The network helps show where James H. Cole may publish in the future.

Co-authorship network of co-authors of James H. Cole

This figure shows the co-authorship network connecting the top 25 collaborators of James H. Cole. A scholar is included among the top collaborators of James H. Cole based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with James H. Cole. James H. Cole is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Bos, Len, James H. Cole, Eva Strijbis, et al.. (2025). Repeatability and reproducibility of brain age estimates in multiple sclerosis for three publicly available models. Neuroimage Reports. 5(2). 100252–100252.

Gupta, Yubraj, Feliberto de la Cruz, Christian Gaser, et al.. (2025). Does restrictive anorexia nervosa impact brain aging? A machine learning approach to estimate age based on brain structure. Computers in Biology and Medicine. 194. 110484–110484. 1 indexed citations

Parker, Chris A. C., et al.. (2025). Rician Likelihood Loss for Quantitative MRI With Self‐Supervised Deep Learning. NMR in Biomedicine. 38(10). e70136–e70136.

Verdi, Serena, Seyed Mostafa Kia, Anna Fitzgerald, et al.. (2024). Alzheimer's disease heterogeneity revealed by neuroanatomical normative modeling. Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring. 16(1). e12559–e12559. 9 indexed citations

Cole, James H., et al.. (2024). Volume and distribution of white matter hyperintensities in rheumatoid arthritis and ulcerative colitis patients. Scientific Reports. 14(1). 32010–32010.

Wood, David, Matthew Townend, Asif Mazumder, et al.. (2024). Optimising brain age estimation through transfer learning: A suite of pre‐trained foundation models for improved performance and generalisability in a clinical setting. Human Brain Mapping. 45(4). e26625–e26625. 11 indexed citations

Verdi, Serena, Saige Rutherford, Charlotte Fraza, et al.. (2024). Personalizing progressive changes to brain structure in Alzheimer's disease using normative modeling. Alzheimer s & Dementia. 20(10). 6998–7012. 6 indexed citations

Barkhof, Frederik, Arturo Brunetti, James H. Cole, et al.. (2024). Assessing brain involvement in Fabry disease with deep learning and the brain‐age paradigm. Human Brain Mapping. 45(5). e26599–e26599. 7 indexed citations

Gaser, Christian, et al.. (2024). A perspective on brain-age estimation and its clinical promise. Nature Computational Science. 4(10). 744–751. 13 indexed citations

10.

Anatürk, Melis, Raihaan Patel, Klaus P. Ebmeier, et al.. (2023). Development and validation of a dementia risk score in the UK Biobank and Whitehall II cohorts. SHILAP Revista de lepidopterología. 26(1). e300719–e300719. 21 indexed citations

11.

Benger, Matthew, David Wood, Jeremy Lynch, et al.. (2023). Factors affecting the labelling accuracy of brain MRI studies relevant for deep learning abnormality detection. SHILAP Revista de lepidopterología. 3. 1251825–1251825. 3 indexed citations

12.

Martin, Sophie, et al.. (2023). Interpretable machine learning for dementia: A systematic review. Alzheimer s & Dementia. 19(5). 2135–2149. 69 indexed citations

13.

Fürtjes, Anna E., Ryan Arathimos, Jonathan R. I. Coleman, et al.. (2023). General dimensions of human brain morphometry inferred from genome‐wide association data. Human Brain Mapping. 44(8). 3311–3323. 15 indexed citations

14.

Verdi, Serena, Seyed Mostafa Kia, Keir Yong, et al.. (2023). Revealing Individual Neuroanatomical Heterogeneity in Alzheimer Disease Using Neuroanatomical Normative Modeling. Neurology. 100(24). e2442–e2453. 30 indexed citations

15.

Cole, James H., Richard E. Daws, Vincent Giampietro, et al.. (2022). Tissue volume estimation and age prediction using rapid structural brain scans. Scientific Reports. 12(1). 11 indexed citations

16.

Lange, Ann‐Marie G. de, Melis Anatürk, Jaroslav Rokicki, et al.. (2022). Mind the gap: Performance metric evaluation in brain‐age prediction. Human Brain Mapping. 43(10). 3113–3129. 82 indexed citations

17.

Ren, Wei, Yunyun Duan, Ningnannan Zhang, et al.. (2022). Brain age gap in neuromyelitis optica spectrum disorders and multiple sclerosis. Journal of Neurology Neurosurgery & Psychiatry. 94(1). 31–37. 11 indexed citations

18.

Vaher, Kadi, Laura de Nooij, Matthew Harris, et al.. (2021). Associations between alcohol use and accelerated biological ageing. Addiction Biology. 27(1). e13100–e13100. 30 indexed citations

19.

Francesco, Davide De, Ferdinand W.N.M. Wit, James H. Cole, et al.. (2018). The ‘COmorBidity in Relation to AIDS’ (COBRA) cohort: Design, methods and participant characteristics. PLoS ONE. 13(3). e0191791–e0191791. 16 indexed citations

20.

Scott, Gregory, Anil Ramlackhansingh, Paul Edison, et al.. (2016). Amyloid pathology and axonal injury after brain trauma. Neurology. 86(9). 821–828. 110 indexed citations

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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