Magnanimous 发表于 2025-3-21 20:00:44
书目名称Interpretability of Machine Intelligence in Medical Image Computing影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0472701<br><br> <br><br>书目名称Interpretability of Machine Intelligence in Medical Image Computing影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0472701<br><br> <br><br>书目名称Interpretability of Machine Intelligence in Medical Image Computing网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0472701<br><br> <br><br>书目名称Interpretability of Machine Intelligence in Medical Image Computing网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0472701<br><br> <br><br>书目名称Interpretability of Machine Intelligence in Medical Image Computing被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0472701<br><br> <br><br>书目名称Interpretability of Machine Intelligence in Medical Image Computing被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0472701<br><br> <br><br>书目名称Interpretability of Machine Intelligence in Medical Image Computing年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0472701<br><br> <br><br>书目名称Interpretability of Machine Intelligence in Medical Image Computing年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0472701<br><br> <br><br>书目名称Interpretability of Machine Intelligence in Medical Image Computing读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0472701<br><br> <br><br>书目名称Interpretability of Machine Intelligence in Medical Image Computing读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0472701<br><br> <br><br>GNAT 发表于 2025-3-21 20:52:10
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,Explainable Artificial Intelligence for Breast Tumour Classification: Helpful or Harmful, of mammograms. The main contribution of this research is the discovery that the 3 techniques consistently disagree both with each other and with the medical truth. We argue that using these off-shelf techniques in a medical context is not a feasible approach, and discuss possible causes of this problem, as well as some potential solutions.迁移 发表于 2025-3-22 11:11:39
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Conference proceedings 2022tion, MICCAI 2022..The 10 full papers presented at iMIMIC 2022 were carefully reviewed and selected from 24 submissions each. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. .摆动 发表于 2025-3-22 19:14:44
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