May 8, 2024, 4:46 a.m. | Junting Zhao, Yang Zhou, Zhihao Chen, Huazhu Fu, Liang Wan

cs.CV updates on arXiv.org arxiv.org

arXiv:2405.04175v1 Announce Type: new
Abstract: Automated radiology reporting holds immense clinical potential in alleviating the burdensome workload of radiologists and mitigating diagnostic bias. Recently, retrieval-based report generation methods have garnered increasing attention due to their inherent advantages in terms of the quality and consistency of generated reports. However, due to the long-tail distribution of the training data, these models tend to learn frequently occurring sentences and topics, overlooking the rare topics. Regrettably, in many cases, the descriptions of rare topics …

abstract advantages arxiv attention automated bias clinical cs.cv diagnostic generated however medical quality radiology report reporting reports retrieval terms type

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