Identifying spatial cellular structures with SPACE-GM

IF 72.5 1区医学 Q1 ONCOLOGY

Nature Reviews Cancer Pub Date : 2023-04-28 DOI:10.1038/s41568-023-00582-6

Zhenqin Wu

引用次数: 0

Abstract

In this Tools of the Trade article, Zhenqin Wu describes the development and use of SPACE-GM, a graph deep learning tool that enables the detection of spatial cellular structures predictive of outcomes of patients with cancer.

查看原文本刊更多论文

利用 SPACE-GM 识别空间细胞结构

在这篇 "贸易工具"（Tools of the Trade）文章中，吴振钦介绍了 SPACE-GM 的开发和使用情况，SPACE-GM 是一种图形深度学习工具，能够检测预测癌症患者预后的空间细胞结构。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Nature Reviews Cancer 医学-肿瘤学

CiteScore

111.90

自引率

0.40%

发文量

审稿时长

6-12 weeks

期刊介绍： Nature Reviews Cancer, a part of the Nature Reviews portfolio of journals, aims to be the premier source of reviews and commentaries for the scientific communities it serves. The correct abbreviation for abstracting and indexing purposes is Nat. Rev. Cancer. The international standard serial numbers (ISSN) for Nature Reviews Cancer are 1474-175X (print) and 1474-1768 (online). Unlike other journals, Nature Reviews Cancer does not have an external editorial board. Instead, all editorial decisions are made by a team of full-time professional editors who are PhD-level scientists. The journal publishes Research Highlights, Comments, Reviews, and Perspectives relevant to cancer researchers, ensuring that the articles reach the widest possible audience due to their broad scope.