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人工智能在新冠病毒超微结构中的应用

Artificial Intelligence in COVID-19 Ultrastructure.

作者信息

Elwazir Mohamed Y, Hosny Somaya

机构信息

Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.

Department of Cardiology, Faculty of Medicine, Suez Canal University, Ismailia, Egypt.

出版信息

J Microsc Ultrastruct. 2020 Dec 10;8(4):146-147. doi: 10.4103/JMAU.JMAU_28_20. eCollection 2020 Oct-Dec.

DOI:10.4103/JMAU.JMAU_28_20
PMID:33623737
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7883503/
Abstract

Artificial intelligence has found its way into numerous fields of medicine in the past decade, spurred by the availability of big data and powerful processors. For the COVID-19 pandemic, aside from predicting its onset, artificial intelligence has been used to track disease spread, detect pulmonary involvement in computed tomography scans, risk-stratify patients, and model virtual protein structure and potential therapeutic agents. This mini-review briefly discusses the potential applications of artificial intelligence in COVID-19 microscopy.

摘要

在过去十年中,受大数据和强大处理器的推动,人工智能已在医学的众多领域得到应用。对于新冠疫情,除了预测其爆发,人工智能还被用于追踪疾病传播、在计算机断层扫描中检测肺部受累情况、对患者进行风险分层,以及模拟虚拟蛋白质结构和潜在治疗药物。这篇综述简要讨论了人工智能在新冠病毒显微镜检查中的潜在应用。

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本文引用的文献

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Pulmonary and cardiac pathology in African American patients with COVID-19: an autopsy series from New Orleans.非裔美国人 COVID-19 患者的肺部和心脏病理学:来自新奥尔良的尸检系列。
Lancet Respir Med. 2020 Jul;8(7):681-686. doi: 10.1016/S2213-2600(20)30243-5. Epub 2020 May 27.
2
AI-Driven Tools for Coronavirus Outbreak: Need of Active Learning and Cross-Population Train/Test Models on Multitudinal/Multimodal Data.人工智能驱动的冠状病毒爆发工具:在多纵向/多模态数据上进行主动学习和跨人群训练/测试模型的需求。
J Med Syst. 2020 Mar 18;44(5):93. doi: 10.1007/s10916-020-01562-1.
3
Artificial Intelligence-Based Mitosis Detection in Breast Cancer Histopathology Images Using Faster R-CNN and Deep CNNs.基于人工智能的乳腺癌组织病理学图像有丝分裂检测:使用更快的区域卷积神经网络和深度卷积神经网络
J Clin Med. 2020 Mar 10;9(3):749. doi: 10.3390/jcm9030749.
4
Deep Semi Supervised Generative Learning for Automated Tumor Proportion Scoring on NSCLC Tissue Needle Biopsies.深度半监督生成式学习在非小细胞肺癌组织穿刺活检肿瘤比例评分中的应用。
Sci Rep. 2018 Nov 26;8(1):17343. doi: 10.1038/s41598-018-35501-5.
5
Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis.深度学习作为提高组织病理学诊断准确性和效率的工具。
Sci Rep. 2016 May 23;6:26286. doi: 10.1038/srep26286.
6
Mitosis detection in breast cancer histological images An ICPR 2012 contest.乳腺癌组织学图像中的有丝分裂检测:一项2012年国际模式识别会议竞赛
J Pathol Inform. 2013 May 30;4:8. doi: 10.4103/2153-3539.112693. Print 2013.
7
Antitumor and immunosuppressive activities of lankacidin-group antibiotics: structure-activity relationships.兰卡杀菌素类抗生素的抗肿瘤和免疫抑制活性:构效关系
Cancer Chemother Rep. 1975 Sep-Oct;59(5):919-28.