Evidence map›Paper›PMID 41878194›Full record

ArticleFrontiers in radiology2026

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

Sofija Jovanović, Jelena Vukićević, Biljana Kilibarda, Marko Milosavljević, Vesna Bjegović-Mikanović

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Article in Frontiers in radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Sofija JovanovićCenter for Radiology, University Clinical Center of Serbia, Belgrade, Serbia.
Jelena VukićevićInstitute of Ethnography of the Serbian Academy of Sciences and Arts, Belgrade, Serbia.
Biljana KilibardaInstitute of Public Health of Serbia "Dr Milan Jovanović Batut", Belgrade, Serbia.
Marko MilosavljevićInstitute of Public Health of Serbia "Dr Milan Jovanović Batut", Belgrade, Serbia.
Vesna Bjegović-MikanovićInstitute of Social Medicine, University of Belgrade, Faculty of Medicine, Belgrade, Serbia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

artificial intelligencebreast cancer screeningfocus groupsmammographyqualitative research

Identifiers

PMID41878194
PMCPMC13006751

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.