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Memorisation bias in medical AI

Paper recorded by Signals 4 on 2026-09-15 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-15 on arXiv · recorded by Signals 4 on 2026-09-16

Category: cs.LG · 机器学习 · first seen 2026-09-16

Abstract

Medical AI models hold immense potential to improve patient outcomes, but they are also known to unintentionally memorise individual records from their training datasets. While such memorisation has been linked to targeted privacy attacks, its consequences for clinical deployment, where patients may be assessed by a model that saw their historical data during training, remain poorly understood. He

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#43 most recent of 215 cs.LG papers we have recorded · ↑ newer: Easy to Catch a Liar, Hard to Clear an Honest One: Language Models Dia · ↓ older: Bellman Policy Optimization
Cite this page: Memorisation bias in medical AI: the #43 most recent of 215 cs.LG papers we have recorded (as of 2026-09-15). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/memorisation-bias-in-medical-ai.html
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