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Evidence record 12 · automatically gathered

Longitudinal Multi-View Breast Cancer Risk Prediction

Accurate breast cancer risk prediction from screening mammography is critical for enabling personalized screening intervals and early detection. Recent deep learning methods have shown the value of longitudinal data and explicit temporal alignment. However, existing approaches either perform explicit alignment using a single mammographic view or model multiple views without explicit longitudinal alignment, limiting their ability to exploit the complementary spatial-temporal information used in c

Record details

Published: 13 July 2026
Source: arXiv
Category: Research
Topics: Safety & alignment
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Safety & alignment

BackgroundMellow: A Multi-Modal Cohesive Framework for Narrative-Driven Rich Cinematic Soundscape Generation

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Shared topic: Safety & alignment

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Shared topic: Safety & alignment

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Shared topic: Safety & alignment

Towards Predictive, Aligned, and Scalable Robot Learning

arXiv · 13 July 2026

Shared topic: Safety & alignment

Trustworthy synthetic data for campaign decision support: strategy simulation fidelity and the PolicySynth framework

arXiv cs.LG · 13 July 2026

Shared topic: Safety & alignment

ManiScope: LLM-Assisted Visual Analytics of Cryptocurrency Manipulation Risk

arXiv cs.HC · 13 July 2026

How to cite this record

ethics.ai (13 July 2026), “Longitudinal Multi-View Breast Cancer Risk Prediction,” evidence record 12, https://ethics.ai/record/12 (originally published by arXiv).

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