Journal article
Perinatal health predictors using artificial intelligence: A review
- Abstract:
-
Advances in public health and medical care have enabled better pregnancy and birth outcomes. The rates of perinatal health indicators such as maternal mortality and morbidity; fetal, neonatal, and infant mortality; low birthweight; and preterm birth have reduced over time. However, they are still a public health concern, and considerable disparities exist within and between countries. For perinatal researchers who are engaged in unraveling the tangled web of causation for maternal and child h...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Authors
Bibliographic Details
- Publisher:
- SAGE Publications Publisher's website
- Journal:
- Women's Health Journal website
- Volume:
- 17
- Pages:
- 1-7
- Publication date:
- 2021-09-14
- Acceptance date:
- 2021-08-26
- DOI:
- EISSN:
-
1745-5065
- ISSN:
-
1745-5057
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
1192719
- Local pid:
- pubs:1192719
- Deposit date:
- 2021-08-26
Terms of use
- Copyright holder:
- Ramakrishnan et al.
- Copyright date:
- 2021
- Rights statement:
- Copyright © 2021 The Author(s). This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
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