# Artificial Intelligence in Radiology: Advancing Precision, Accuracy, and Early Detection in Cancer Diagnosis

## TL;DR

This paper reviews how AI is improving cancer diagnosis through radiology, focusing on early detection and personalized care.

## Contribution

The paper provides a thematic synthesis of AI in radiology, organizing evidence into cross-cutting frameworks for cancer care.

## Key findings

- AI enhances precision imaging and early cancer detection.
- Multimodal data integration improves disease characterization.
- Model explainability and equity are critical for AI adoption in radiology.

## Abstract

Artificial intelligence (AI) is rapidly transforming oncologic radiology, enabling earlier detection, greater precision, and more personalized care. Yet much of the literature remains fragmented into disease-specific studies or narrow performance assessments. This review addresses that gap through a narrative thematic synthesis of research published between 2019 and 2025, identified from major biomedical and engineering databases and selected for clinical relevance, translational value, and policy significance. Unlike prior reviews that catalog isolated applications, it organizes evidence into cross-cutting frameworks that redefine radiology’s role in cancer care. These include advances in precision imaging and early detection, the integration of multimodal data for richer disease characterization, and the use of AI in prognosis and treatment monitoring. Equally, the review highlights challenges of model explainability, federated learning, equity, and workforce adaptation as determinants of adoption. By situating these themes within Clinical Decision Support Systems (CDSS) and broader healthcare infrastructures, the analysis shows that AI’s significance lies less in isolated accuracy gains than in its transparency, inclusivity, and adaptability across contexts. The review concludes that the decisive priority now is to build global collaborations, robust validation, and ethical frameworks that ensure AI evolves as an inclusive ecosystem capable of delivering equitable improvements in cancer care worldwide.