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

Background: 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. Methods: 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. Results: 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. Conclusions: 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.

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Journal
Digital Archive of SASA (Serbian Academy of Sciences and Arts)
Published
2026-02-24
DOI
https://doi.org/10.3389/fradi.2026.1714029/full
Primary Topic
AI in cancer detection
Type
article
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article

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

Vesna M. Bjegovic-Mikanovic, Sofija Jovanović, Jelena Pavičić Vukičević, Biljana Kilibarda et al.
Digital Archive of SASA (Serbian Academy of Sciences and Arts)
AI in cancer detection
article

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

Vesna M. Bjegovic-Mikanovic, Sofija Jovanović, Jelena Pavičić Vukičević, Biljana Kilibarda, Marko Milosavljević
article en

Abstract

Background: 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. Methods: 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. Results: 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. Conclusions: 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.

Digital Archive of SASA (Serbian Academy of Sciences and Arts)
Serbian Academy of Sciences and Arts (RS), University of Belgrade (RS), Institute of Social Sciences (RS), Centar za Promociju Nauke (RS), Institute of Public Health of Serbia (RS)
Openalex Percentile: Top 28%
AI in cancer detection
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