Work

Prediction to Policy decision: The evolving role of artificial intelligence in public health

Year: 2026

Type: article

Abstract: Problem considered Artificial intelligence (AI) is increasingly shaping public health through its ability to analyze complex datasets for surveillance, prediction, and decision making. Advances in machine learning, deep learning, and natural language processing have assisted AI in disease monitoring, diagnostics, and health system management. But concerns regarding data governance, ethics, and equity remain. This narrative review was aimed to integrate current evidence of AI in public health, technological approaches, programmatic experiences, and challenges. Methods A narrative literature review was conducted using a structured search using electronic databases including PubMed, Scopus, and Google Scholar for relevant articles. Policy documents from international and national organizations like the WHO, Centers for Disease Control and Prevention, and the ICMR were also reviewed. Peer-reviewed articles, narrative reviews, ethical guidelines were identified, screened and were included. Results Applications of AI were identified across several public health domains. Digital epidemiology tools have shown potential for early outbreak detection. AI models have improved diagnostic performance in many fields like TB and cancer screening. Digital health platforms in India illustrate the growing use of digital infrastructure and data driven approaches in public health programme, while selected AI-supported applications are emerging in specific areas. Challenges related to data quality, transparency, privacy, and workforce capacity remain barriers to large scale implementation. Conclusion AI has the potential to strengthen public health systems by improving surveillance, diagnostics, and decision-making. Responsible integration requires strong data governance, ethical oversight, interdisciplinary collaboration, and investment in digital infrastructure to ensure equitable and sustainable public health impact.

Source: Clinical Epidemiology and Global Health

DOI: 10.1016/j.cegh.2026.102514

Authors: S.R. Sreedevi, D.N. Sindhura, Ramesh Holla, Mithun Rao, Ajay Mallya, Bhaskaran Unnikrishnan

Institutions: Manipal Academy of Higher Education, Kasturba Medical College, Mangalore, Kasturba Medical College, Manipal

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,000