AI-based BRAIx risk score for the intermediate-term prediction of breast cancer: a population cohort study

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The AI-based BRAIx risk score predicts intermediate-term breast cancer risk in a population cohort. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

Helen M L Frazer; John L Hopper; Tuong L. Nguyen; Michael S Elliott; Katrina M Kunicki; Osamah Al-Qershi; Daniel F Schmidt; Enes Makalic; Shuai Li (65944); Samantha K Fox; James G Dowty; Carlos A Peña-Solorzano; Chun Fung Kwok; Yuanhong Chen; Chong Wang; Joel Symonds; Peter Brotchie; Gustavo Carneiro; Fredrik Strand; Davis J McCarthy

doi:10.1016/j.landig.2026.100987

Key Points

This research aims to develop an AI-based risk score for predicting breast cancer in the intermediate term.
Utilized a population cohort with diverse demographics.
Developed an AI algorithm to calculate the BRAIx risk score.
Conducted validation of the risk score against historical data.
The BRAIx risk score showed significant accuracy in predicting breast cancer risk.
Improved intermediate-term prediction compared to traditional methods.

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Implication

Population cohort study demonstrates improved prediction of breast cancer risk, suggesting enhanced screening strategies.

Abstract

Australian Government Medical Research Future Fund, the Ramaciotti Foundation, the National Breast Cancer Foundation, Cancer Australia, and the National Health and Medical Research Council.

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Cite This Study

Frazer et al. (2026) studied this question.

synapsesocial.com/papers/69abc0925af8044f7a4e935f https://doi.org/10.1016/j.landig.2026.100987

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AI-based BRAIx risk score for the intermediate-term prediction of breast cancer: a population cohort study

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Cite This Study

AI-based BRAIx risk score for the intermediate-term prediction of breast cancer: a population cohort study

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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