Journal article
Image analysis and machine learning for detecting malaria
- Abstract:
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Malaria remains a major burden on global health, with roughly 200 million cases worldwide and more than 400,000 deaths per year. Besides biomedical research and political efforts, modern information technology is playing a key role in many attempts at fighting the disease. One of the barriers toward a successful mortality reduction has been inadequate malaria diagnosis in particular. To improve diagnosis, image analysis software and machine learning methods have been used to quantify parasite...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Version of record, pdf, 1.3MB)
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- Publisher copy:
- 10.1016/j.trsl.2017.12.004
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Authors
Funding
National Institutes of Health
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Wellcome Trust
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Bibliographic Details
- Publisher:
- Elsevier Publisher's website
- Journal:
- Translational Research Journal website
- Volume:
- 194
- Pages:
- 36-55
- Publication date:
- 2018-01-01
- Acceptance date:
- 2017-12-19
- DOI:
- EISSN:
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1878-1810
- ISSN:
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1931-5244
- Source identifiers:
-
825593
Item Description
- Keywords:
- Pubs id:
-
pubs:825593
- UUID:
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uuid:6532e962-5320-44eb-b176-d93778771a8a
- Local pid:
- pubs:825593
- Deposit date:
- 2018-03-02
Terms of use
- Copyright holder:
- Maude et al
- Copyright date:
- 2018
- Notes:
- Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
- Licence:
- CC Attribution (CC BY)
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