难受
发表于 2025-3-21 17:05:02
书目名称Ethics and Fairness in Medical Imaging影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0320731<br><br> <br><br>书目名称Ethics and Fairness in Medical Imaging影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0320731<br><br> <br><br>书目名称Ethics and Fairness in Medical Imaging网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0320731<br><br> <br><br>书目名称Ethics and Fairness in Medical Imaging网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0320731<br><br> <br><br>书目名称Ethics and Fairness in Medical Imaging被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0320731<br><br> <br><br>书目名称Ethics and Fairness in Medical Imaging被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0320731<br><br> <br><br>书目名称Ethics and Fairness in Medical Imaging年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0320731<br><br> <br><br>书目名称Ethics and Fairness in Medical Imaging年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0320731<br><br> <br><br>书目名称Ethics and Fairness in Medical Imaging读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0320731<br><br> <br><br>书目名称Ethics and Fairness in Medical Imaging读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0320731<br><br> <br><br>
表示问
发表于 2025-3-21 22:52:25
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Subdue
发表于 2025-3-22 02:06:24
https://doi.org/10.1007/978-1-4614-1854-2e performance across various demographic groups. However, their performance varies strongly across nodule characteristics (size and type) in line with their prevalence in the training set. To ensure continued equitable performance, algorithms should not only consider demographic but also nodule attributes representativeness in their training.
现任者
发表于 2025-3-22 04:39:46
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irreducible
发表于 2025-3-22 12:07:02
https://doi.org/10.1007/978-3-658-14777-8forming impact assessments of sociotechnical harms can assist in operationalizing the medical ethics principle of non-maleficence, thereby guiding the ethical development and implementation of AI technologies in healthcare.
GOUGE
发表于 2025-3-22 15:58:14
https://doi.org/10.1007/978-3-319-31287-3ectual property, and data ownership. Furthermore, we discuss regulations governing the use of synthetic medical data. To promote equitable application of these powerful tools, we also propose clear guidelines for promoting fairness, mitigating bias, and ensuring diversity within generative AI models.
GOUGE
发表于 2025-3-22 20:41:27
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synovitis
发表于 2025-3-23 00:06:20
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Cholesterol
发表于 2025-3-23 01:45:57
On Biases in a UK Biobank-Based Retinal Image Classification Modelresponds differently to the mitigation methods. We also find that these methods are largely unable to enhance fairness, highlighting the need for better bias mitigation methods tailored to the specific type of bias.
斥责
发表于 2025-3-23 07:27:42
Assessing the Impact of Sociotechnical Harms in AI-Based Medical Image Analysisforming impact assessments of sociotechnical harms can assist in operationalizing the medical ethics principle of non-maleficence, thereby guiding the ethical development and implementation of AI technologies in healthcare.