Application of machine learning in early childhood development research: a scoping review
Background Early childhood development (ECD) lays the foundation for lifelong health, academic success and social well-being, yet over 250 million children in low- and middle-income countries are at risk of not reaching their developmental potential. Traditional measures fail to fully capture the ri...
Saved in:
| Main Authors: | Akbar K Waljee, Amina Abubakar, Patrick N Mwangala, Faith Neema Benson, Daisy Chelangat, Willie Brink, Cheryl A Moyer |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMJ Publishing Group
2025-08-01
|
| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/15/8/e100358.full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Prevalence and associated factors of mental and substance use problems among adults in Kenya: A community-based cross-sectional study.
by: Patrick Nzivo Mwangala, et al.
Published: (2025-01-01) -
Inequities in childhood cancer research: A scoping review
by: Jean Hunleth, et al.
Published: (2024-12-01) -
Risk and protective factors in early childhood development: a scoping review
by: Isabela Melo Martins, et al.
Published: (2025-04-01) -
Exploring early childhood development programming in Kenya’s arid and semi-arid lands
by: Phyllis Magoma, et al.
Published: (2025-06-01) -
Mental health and well-being of older adults living with HIV in sub-Saharan Africa: a systematic review
by: Charles R J C Newton, et al.
Published: (2021-09-01)