DIGITAL HEALTH TECHNOLOGIES FOR THE INTEGRATED VISUALISATION AND PREDICTION OF MATERNAL HEALTH: INTEGRATING PREDICTIVE ANALYTICS, SAFE NUTRITION, AND PREGNANCY CARE

Authors

  • Saba Mohauddin Lahore Leads University, Pakistan. Author
  • Dr Bilal Mehboob Lahore Leads University, Pakistan. Author
  • Dr Anum Ali Lahore Leads University, Pakistan. Author https://orcid.org/0000-0003-4811-7171

DOI:

https://doi.org/10.71146/kjmr1034

Keywords:

Maternal health, pregnancy mortality, digital healthcare, monitoring

Abstract

The rapid evolution of digital health technologies (DHTs) presents unprecedented opportunities to mitigate maternal mortality and morbidity, particularly in resource-constrained environments. However, current interventions often operate in technological silos, failing to integrate crucial components such as clinical risk prediction, nutritional monitoring for safe food consumption, and culturally grounded patient interaction. This paper proposes a comprehensive, multi-modal framework that synergizes predictive analytics, explainable artificial intelligence (XAI), and continuous health monitoring to support pregnancy care. By integrating predictive models capable of analyzing temporal health data with visualization dashboards designed for clinical trust, the proposed system aims to provide actionable insights for maternal health and gestational nutrition. Ultimately, this approach bridges the gap between complex algorithmic outputs and the practical, socio-cultural realities of expectant mothers, paving the way for more holistic and effective digital healthcare interventions.

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Author Biography

  • Dr Anum Ali, Lahore Leads University, Pakistan.

    Professor of Computing and Engineering, Entepreneurship, mama of three girls by grace of god. 

References

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Published

2026-03-31

Issue

Section

Computer Science

How to Cite

DIGITAL HEALTH TECHNOLOGIES FOR THE INTEGRATED VISUALISATION AND PREDICTION OF MATERNAL HEALTH: INTEGRATING PREDICTIVE ANALYTICS, SAFE NUTRITION, AND PREGNANCY CARE. (2026). Kashf Journal of Multidisciplinary Research, 3(03), 38-44. https://doi.org/10.71146/kjmr1034