This paper is in the following e-collection/theme issue:

Non-randomized Protocols and Methods (ehealth) (671) Big Data (307) Machine Learning (2074) Mobile Health and Apps for Maternal and Child Health (215)

Published on in Vol 8, No 5 (2019): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11456, first published .
Use of Big Data and Machine Learning Methods in the Monitoring and Evaluation of Digital Health Programs in India: An Exploratory Protocol

Use of Big Data and Machine Learning Methods in the Monitoring and Evaluation of Digital Health Programs in India: An Exploratory Protocol

Use of Big Data and Machine Learning Methods in the Monitoring and Evaluation of Digital Health Programs in India: An Exploratory Protocol

Authors of this article:

Diwakar Mohan1 Author Orcid Image ;   Jean Juste Harrisson Bashingwa2 Author Orcid Image ;   Pierre Dane3 Author Orcid Image ;   Sara Chamberlain4 Author Orcid Image ;   Nicki Tiffin2, 5 Author Orcid Image ;   Amnesty Lefevre1, 3 Author Orcid Image
Article Authors Cited by (10) Tweetations (8) Metrics

Journals

  1. Shah N, Mohan D, Bashingwa J, Ummer O, Chakraborty A, LeFevre A. Using Machine Learning to Optimize the Quality of Survey Data: Protocol for a Use Case in India. JMIR Research Protocols 2020;9(8):e17619 View
  2. Oprescu A, Miro-Amarante G, Garcia-Diaz L, Beltran L, Rey V, Romero-Ternero M. Artificial Intelligence in Pregnancy: A Scoping Review. IEEE Access 2020;8:181450 View
  3. Bashingwa J, Mohan D, Chamberlain S, Arora S, Mendiratta J, Rahul S, Chauhan V, Scott K, Shah N, Ummer O, Ved R, Mulder N, LeFevre A. Assessing exposure to Kilkari: a big data analysis of a large maternal mobile messaging service across 13 states in India. BMJ Global Health 2021;6(Suppl 5):e005213 View
  4. Gutiérrez-Aguado A, Curioso W, Machicao J, Eguia H. Strengthening capacities of multidisciplinary professionals to apply data science in public health: Experience of an international graduate diploma program in Peru. International Journal of Medical Informatics 2023;169:104913 View
  5. Bashingwa J, Mohan D, Chamberlain S, Scott K, Ummer O, Godfrey A, Mulder N, Moodley D, LeFevre A. Can we design the next generation of digital health communication programs by leveraging the power of artificial intelligence to segment target audiences, bolster impact and deliver differentiated services? A machine learning analysis of survey data from rural India. BMJ Open 2023;13(3):e063354 View
  6. El Burai Felix S, Yusuf H, Ritchey M, Romano S, Namulanda G, Wilkins N, Boehmer T. A Standard Framework for Evaluating Large Health Care Data and Related Resources. MMWR Supplements 2024;73(3):1 View
  7. Bouyousfi S, Ouedraogo M. Artificial intelligence and big data-driven evaluation research and practices: A systematic literature review. Evaluation 2025;31(3):303 View

Books/Policy Documents

  1. Rawat S, Rana S, Lamba G, Shweta Mongia , Singh T. Revolutionizing Business Practices Through Artificial Intelligence and Data-Rich Environments. View

Conference Proceedings

  1. Madamombe T, Kasiroori J, Pillay S. 2024 3rd Zimbabwe Conference of Information and Communication Technologies (ZCICT). A Systematic Review of Challenges and Opportunities in Integrating Big Data for Monitoring and Evaluation in Global Development Programmes View
  2. Madamombe T, Kasiroori J, Pillay S, Chirau T. 2025 IEEE International Conference on AI and Data Analytics (ICAD). A Delphi-Driven Ontology for Integrating Big Data in Monitoring and Evaluation View