English(EN) Responsible Integration of AI in Cancer Genomics: Barriers, Risks, and Pathways to Trustworthy Clinical Translation

癌症基因组学中的人工智能：已识别的障碍、风险和值得信赖的整合途径

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-01 04:00

一篇新的arXiv论文详细介绍了将人工智能和自然语言处理整合到癌症基因组学中的挑战和潜在解决方案。该综述确定了四个关键的失败领域：证据不一致、可解释性问题、数据治理问题和互操作性挑战。为了克服这些问题，作者提出了一个强调严格验证、不确定性感知方法、可互操作的基础设施、监管一致性以及在整个AI生命周期中持续的人工监督的框架。 AI

影响解决了在临床环境中采用人工智能的关键障碍，有可能加速人工智能工具在医疗保健领域值得信赖的转化。

排序理由该集群包含一篇发表在arXiv上的研究论文，详细介绍了人工智能在特定领域的应用和挑战。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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Signal score: 35 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Bahar \.Ilgen, Yiannos Tolias, Denise K\"uhnert, Paraskevi Papadopoulou, Magnus Westerlund, Dominik Heider, Katharina Ladewig, Georges Hattab · 2026-09-01 04:00

人工智能在癌症基因组学中的负责任整合：障碍、风险与可信临床转化之路

arXiv:2608.30912v1 Announce Type: new Abstract: Artificial intelligence (AI) and natural language processing (NLP) are increasingly used to extract, integrate, and interpret biomedical knowledge relevant to cancer genomics, yet their translation into routine clinical oncology has…

本文如何被排名

报道来源 [1]

人工智能在癌症基因组学中的负责任整合：障碍、风险与可信临床转化之路

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