Predicting Adverse Neonatal Outcomes for Preterm Neonates with Multi-Task Learning
Predicting Adverse Neonatal Outcomes for Preterm Neonates with Multi-Task Learning
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Diagnosis of adverse neonatal outcomes is crucial for preterm survival since it enables doctors to provide timely treatment. Machine learning (ML) algorithms have been demonstrated to be effective in predicting adverse neonatal outcomes. However, most previous ML-based methods have only focused on predicting a single outcome, ignoring the potential...
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Predicting Adverse Neonatal Outcomes for Preterm Neonates with Multi-Task Learning
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TN_cdi_proquest_journals_2792172688
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2792172688
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E-ISSN
2331-8422
