更正：利用深度学习模型评估恶性白斑切除边缘的黑素细胞密度。

IF 2.4 3区医学 Q2 PATHOLOGY

Diagnostic Pathology Pub Date : 2024-09-05 DOI:10.1186/s13000-024-01545-7

Jan Siarov, Darshan Kumar, John Paoli, Johan Mölne, Martin Gillstedt, Noora Neittaanmäki

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Correction: Utilizing deep learning model for assessing melanocytic density in resection margins of lentigo maligna.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Diagnostic Pathology 医学-病理学

CiteScore

4.60

自引率

0.00%

发文量

审稿时长

1 months

期刊介绍： Diagnostic Pathology is an open access, peer-reviewed, online journal that considers research in surgical and clinical pathology, immunology, and biology, with a special focus on cutting-edge approaches in diagnostic pathology and tissue-based therapy. The journal covers all aspects of surgical pathology, including classic diagnostic pathology, prognosis-related diagnosis (tumor stages, prognosis markers, such as MIB-percentage, hormone receptors, etc.), and therapy-related findings. The journal also focuses on the technological aspects of pathology, including molecular biology techniques, morphometry aspects (stereology, DNA analysis, syntactic structure analysis), communication aspects (telecommunication, virtual microscopy, virtual pathology institutions, etc.), and electronic education and quality assurance (for example interactive publication, on-line references with automated updating, etc.).