# Artificial intelligence and breast cancer screening in Serbia: a dual-perspective qualitative study among radiologists and screening-aged women

## TL;DR

This study explores how radiologists and women in Serbia view the use of artificial intelligence in breast cancer screening, aiming to improve public health strategies.

## Contribution

The study is the first to investigate Serbian radiologists and women's perspectives on AI in breast cancer screening.

## Key findings

- Radiologists in Serbia have a cautiously positive attitude toward using AI in mammography screening.
- Women's support for AI in screening depends on its ability to improve healthcare outcomes.
- The study highlights the need for further research to fully understand attitudes toward AI in breast cancer screening in Serbia.

## Abstract

Breast cancer screening (BCS) by mammography was introduced globally in the last decades of the previous century and has been implemented in opportunistic or population-based models worldwide ever since. In Serbia, the national BCS Program was established in late 2012. Despite its existing framework, the Program's coverage remains suboptimal, and novel approaches to its optimization are being explored. The increasing use of artificial intelligence (AI) technology in numerous fields has been a hallmark of the previous decade, with AI-based solutions in breast imaging at the forefront of many research initiatives. Qualitative research has been previously conducted from Australia to Sweden, yielding insights into the AI-radiologist interaction, as well as the acceptability of screening-aged women toward AI use in screening. This study aims to gauge the stakeholders’ perspectives—radiologists’ and women's—on AI use in BCS in Serbia and help inform policy adaptations to maximize the prospective effectiveness of this public health intervention.

Four focus groups (FGs) were organized in total, two with radiologists and two with screening-aged women, in Belgrade and Novi Sad. Residents in training and radiology specialists were divided for maximal discussion liberty. Two research members analyzed the discussion transcripts using a mixed inductive-deductive approach with a flexible coding frame.

Radiologists in this study see room for and have an overall cautiously positive attitude toward the application of AI in mammography BCS in the future. If AI were to perceptibly improve the current state of healthcare, such use of AI could be met with support among BCS-aged women.

This study represents the first step towards understanding the attitudes of radiologists and screening-aged women in Serbia towards the use of AI in mammography. Additional studies will be necessary to get a more comprehensive overview.