Journal article
Challenges for machine learning in clinical translation of big data imaging studies
- Abstract:
- Combining deep learning image analysis methods and large-scale imaging datasets offers many opportunities to neuroscience imaging and epidemiology. However, despite these opportunities and the success of deep learning when applied to a range of neuroimaging tasks and domains, significant barriers continue to limit the impact of large-scale datasets and analysis tools. Here, we examine the main challenges and the approaches that have been explored to overcome them. We focus on issues relating to data availability, interpretability, evaluation, and logistical challenges and discuss the problems that still need to be tackled to enable the success of “big data” deep learning approaches beyond research.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
-
-
(Preview, Accepted manuscript, pdf, 1000.5KB, Terms of use)
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- Publisher copy:
- 10.1016/j.neuron.2022.09.012
Authors
- Publisher:
- Cell Press
- Journal:
- Neuron More from this journal
- Volume:
- 110
- Issue:
- 23
- Pages:
- 3866-3881
- Publication date:
- 2022-10-10
- Acceptance date:
- 2022-10-01
- DOI:
- EISSN:
-
1097-4199
- ISSN:
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0896-6273
- Language:
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English
- Keywords:
- Pubs id:
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1282865
- Local pid:
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pubs:1282865
- Deposit date:
-
2022-10-13
- ARK identifier:
Terms of use
- Copyright holder:
- Elsevier Inc.
- Copyright date:
- 2022
- Rights statement:
- © 2022 Elsevier Inc.
- Notes:
- This is the author accepted manuscript following peer review version of the article. The final version is available online from Cell Press at https://dx.doi.org/10.1016/j.neuron.2022.09.012
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