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New framework improves mammography risk prediction using historical data

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new framework called SEM-HD (Single-Exam Mammography risk prediction with privileged History Distillation) to improve breast cancer risk prediction using mammography data. This method leverages longitudinal history as privileged information during training, allowing models to maintain predictive accuracy even when prior examinations are unavailable during deployment. SEM-HD has demonstrated consistent improvements in AUC and pAUC across multiple datasets, particularly at low false-positive rates, by preserving the temporal modeling structure. AI

IMPACT This framework could enhance the accuracy and efficiency of breast cancer risk assessment in clinical settings.

RANK_REASON The cluster contains a research paper detailing a new framework for risk prediction in mammography. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New framework improves mammography risk prediction using historical data

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The cluster contains a research paper detailing a new framework for risk prediction in mammography. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Banafsheh Karimian, Soufiane Belharbi, Alexis Guichemerre, Luke McCaffrey, Mohammadhadi Shateri, Eric Granger ·

    Longitudinal Risk Prediction in Mammography with Privileged History Distillation

    arXiv:2603.15814v2 Announce Type: replace Abstract: Longitudinal mammography screening has become an important source of information for improving future breast cancer risk prediction. However, the performance of current longitudinal mammography models degrades when prior examina…

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