Machine learning prediction of gestational age from metabolic screening markers resistant to ambient temperature transportation: Facilitating use of this technology in low resource settings of South Asia and East Africa-Reference-Cited by-同舟云学术

Machine learning prediction of gestational age from metabolic screening markers resistant to ambient temperature transportation: Facilitating use of this technology in low resource settings of South Asia and East Africa

Published:2022-04-23 Issue: Volume:12 Page:
ISSN:2047-2978
Container-title:Journal of Global Health
language:
Short-container-title:J Glob Health

Author:

Sazawal Sunil¹²,Das Sayan¹,Ryckman Kelli K³,Khanam Rasheda⁴,Nisar Imran⁵,Deb Saikat¹²,Jasper Elizabeth A³,Rahman Sayedur⁶,Mehmood Usma⁵,Dutta Arup¹,Chowdhury Nabidul Haque⁶,Barkat Amina⁵,Mittal Harshita¹,Ahmed Salahuddin⁶,Khalid Farah⁵,Ali Said Mohammed²,Raqib Rubhana⁷,Ilyas Muhammad⁵,Nizar Ambreen⁵,Manu Alexander⁸,Russell Donna⁹,Yoshida Sachiyo⁸,Baqui Abdullah H⁴,Jehan Fyezah⁵,Dhingra Usha¹,Bahl Rajiv⁸

Affiliation:

1. Center for Public Health Kinetics, New Delhi, India

2. Public Health Laboratory-IDC, Chake Chake, Tanzania

3. University of Iowa, Iowa City, Iowa, USA

4. Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA

5. Aga Khan University, Karachi, Pakistan

6. Projahnmo Research Foundation, Dhaka, Bangladesh

7. International Center for Diarrheal Disease Research, Dhaka, Bangladesh

8. Department of Maternal, Newborn, Child and Adolescent Health, and Ageing, Geneva, Switzerland

9. University of California, Seattle, Washington, USA

Publisher

International Global Health Society