Automated machine learning for endemic active tuberculosis prediction from multiplex serological data
Abstract Serological diagnosis of active tuberculosis (TB) is enhanced by detection of multiple antibodies due to variable immune responses among patients. Clinical interpretation of these complex datasets requires development of suitable algorithms, a time consuming and tedious undertaking addresse...
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Auteurs principaux: | Hooman H. Rashidi, Luke T. Dang, Samer Albahra, Resmi Ravindran, Imran H. Khan |
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Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
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Accès en ligne: | https://doaj.org/article/4053b9a7594e4b98a4c70d5817cb61b7 |
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