ARTIFICIAL INTELLIGENCE FOR GLOBAL CANCER PREVENTION: FROM DIGITAL EXPOSOMICS TO EQUITABLE, PREDICTIVE ONCOLOGY

Abstract

Artificial intelligence (AI) plays a considerable transformative role in cancer prevention and early cancer detection. With its potential, it significantly improves survival rates and reduces the burden on healthcare systems. It can analyze vast amounts of data to identify risks and detect, diagnose, and predict cancer with greater speed, accuracy, and consistency than traditional methods. It has substantially changed the standard diagnostic approach by switching it from reactive, symptom-based diagnosis to proactive, AI-assisted screening. Its algorithms are designed to analyze medical images (X-rays, CT scans, MRIs, and mammograms) to detect, localize, and segment tumor-like structures with higher efficiency and greater accuracy. AI shifts conventional cancer prevention methods to "precision prevention" by analyzing an individual's unique data rather than relying on population averages. With its models, it can analyze Electronic Health Records (EHRs) to identify patients at high risk for specific cancers, even years before traditional symptoms appear. It bridges the gap in access to high-quality care, particularly in underserved or rural areas where access to specialists is limited. It integrates genetic data, lifestyle factors, and environmental data to calculate a personalized, 5-year risk score for developing cancer, allowing for earlier and more focused interventions. As a powerful tool that enhances human expertise, enabling early detection, personalized risk assessment, and improved access to screening, AI is already becoming an indispensable ally in the fight against cancer.

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