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

Vaccination and Immunization in the Digital Age (378) Connected Health Conference 2017 (2) Parent and Caregiver Education and Behavior Change for Vaccination (75)

Published on in Vol 4, No 3 (2018): Jul-Sept

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9681, first published .
Using Predictive Analytics to Identify Children at High Risk of Defaulting From a Routine Immunization Program: Feasibility Study

Using Predictive Analytics to Identify Children at High Risk of Defaulting From a Routine Immunization Program: Feasibility Study

Using Predictive Analytics to Identify Children at High Risk of Defaulting From a Routine Immunization Program: Feasibility Study

Authors of this article:

Subhash Chandir1, 2 Author Orcid Image ;   Danya Arif Siddiqi3 Author Orcid Image ;   Owais Ahmed Hussain4 Author Orcid Image ;   Tahira Niazi4 Author Orcid Image ;   Mubarak Taighoon Shah3 Author Orcid Image ;   Vijay Kumar Dharma3 Author Orcid Image ;   Ali Habib4 Author Orcid Image ;   Aamir Javed Khan3 Author Orcid Image
Article Authors Cited by (19) Tweetations (3) Metrics

Journals

  1. Qazi S, Usman M, Mahmood A. A data-driven framework for introducing predictive analytics into expanded program on immunization in Pakistan. Wiener klinische Wochenschrift 2021;133(13-14):695 View
  2. Schwalbe N, Wahl B. Artificial intelligence and the future of global health. The Lancet 2020;395(10236):1579 View
  3. Cutts F, Danovaro-Holliday M, Rhoda D. Challenges in measuring supplemental immunization activity coverage among measles zero-dose children. Vaccine 2021;39(9):1359 View
  4. Qazi S, Usman M. Critical Review of Data Analytics Techniques used in the Expanded Program on Immunization (EPI). Current Medical Imaging Formerly Current Medical Imaging Reviews) 2021;17(1):39 View
  5. Sameen F, Momin Kazi A, Kazmi M, A Abbasi M, Ahmed Qazi S, K Stergioulas L. Improving Routine Immunization Coverage Through Optimally Designed Predictive Models. Computers, Materials & Continua 2022;70(1):375 View
  6. Qazi S, Usman M, Mahmood A, Afzaal Abbasi A, Attique M, Nam Y. Smart Healthcare Using Data-Driven Prediction of Immunization Defaulters in Expanded Program on Immunization (EPI). Computers, Materials & Continua 2020;66(1):589 View
  7. Carrieri V, Lagravinese R, Resce G. Predicting vaccine hesitancy from area‐level indicators: A machine learning approach. Health Economics 2021;30(12):3248 View
  8. Biswas A, Tucker J, Bauhoff S. Performance of predictive algorithms in estimating the risk of being a zero-dose child in India, Mali and Nigeria. BMJ Global Health 2023;8(10):e012836 View
  9. Demsash A, Chereka A, Walle A, Kassie S, Bekele F, Bekana T, Enyew E. Machine learning algorithms’ application to predict childhood vaccination among children aged 12–23 months in Ethiopia: Evidence 2016 Ethiopian Demographic and Health Survey dataset. PLOS ONE 2023;18(10):e0288867 View
  10. Bui H, Ekşioğlu S, Proano R, Nurre Pinkley S. An analysis of COVID-19 vaccine hesitancy in the U.S.. IISE Transactions 2025;57(3):246 View
  11. Tadese Z, Nigatu A, Yehuala T, Sebastian Y. Prediction of incomplete immunization among under-five children in East Africa from recent demographic and health surveys: a machine learning approach. Scientific Reports 2024;14(1) View
  12. Abukhadijah H, Nashwan A. Transforming Hospital Quality Improvement Through Harnessing the Power of Artificial Intelligence. Global Journal on Quality and Safety in Healthcare 2024;7(3):132 View
  13. Mechael P, Gilani S, Ahmad A, LeFevre A, Mohan D, Memon A, Shah M, Siddiqi D, Chandir S, Soundardjee R. Evaluating the “Zindagi Mehfooz” Electronic Immunization Registry and Suite of Digital Health Interventions to Improve the Coverage and Timeliness of Immunization Services in Sindh, Pakistan: Mixed Methods Study. Journal of Medical Internet Research 2024;26:e52792 View
  14. Nantongo B, Nabukenya J, Nabende P, Kamulegeya J. A retrospective cohort study on predicting infants at a risk of defaulting routine immunization in Uganda using machine learning models. JAMIA Open 2024;7(4) View

Books/Policy Documents

  1. Catania L. Foundations of Artificial Intelligence in Healthcare and Bioscience. View
  2. Malhotra A, Borkar P, Chowdhary R, Singh S. Advanced Methods in Biomedical Signal Processing and Analysis. View
  3. Sahadevan D, Al Ali H, Khan M. Information System Design: AI and ML Applications. View