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Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer.深度学习可直接从胃肠道癌症的组织学预测微卫星不稳定性。
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Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning.基于深度学习的非小细胞肺癌组织病理学图像分类和突变预测。
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Automated Gleason grading of prostate cancer tissue microarrays via deep learning.基于深度学习的前列腺癌组织微阵列 Gleason 分级自动化。
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人工智能推动下的精准病理诊断发展新趋势

[New Trends of Development in Precision Pathological Diagnosis Promoted by Artificial Intelligence].

作者信息

Bu Hong

机构信息

Institute of Clinical Pathology/Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China.

出版信息

Sichuan Da Xue Xue Bao Yi Xue Ban. 2021 Mar;52(2):153-155. doi: 10.12182/20210360206.

DOI:10.12182/20210360206
PMID:33829683
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10408910/
Abstract

Precision pathological diagnosis plays a vital role in precision medicine. Both the limited resources available to pathologists and the incessant demands for further refinement and quantification of clinical diagnosis are posing new challenges for pathologists to meet the needs for precision pathological diagnosis. It is expected that artificial intelligence (AI) will be the powerful tool that will help find solutions to this problem from different angles. The author of this article elaborated on a number of ways in which AI can help promote precision pathological diagnosis, including AI-assisted precision extraction of tissue samples, AI-assisted precision histopathologic diagnosis, AI-assisted histological grading and quantitative scoring, AI-assisted precision assessment of tumor biomarkers, AI-assisted prediction of molecular features and precision interpretation of biological information based on hematoxylin-eosin (HE) stained images, the realization of in-depth precision diagnosis based on AI-assisted information integration, and AI-assisted accurate prediction of patient survival and prognosis based on HE-stained images. The paper presents to the readers the future of smart pathology that AI will help usher in.

摘要

精准病理诊断在精准医学中起着至关重要的作用。病理学家可用资源有限,且对临床诊断进一步细化和量化的需求不断增加,这给病理学家带来了新的挑战,以满足精准病理诊断的需求。预计人工智能(AI)将成为从不同角度帮助解决这一问题的有力工具。本文作者阐述了人工智能有助于促进精准病理诊断的多种方式,包括人工智能辅助组织样本的精准提取、人工智能辅助精准组织病理学诊断、人工智能辅助组织学分级和定量评分、人工智能辅助肿瘤生物标志物的精准评估、基于苏木精-伊红(HE)染色图像的人工智能辅助分子特征预测和生物信息精准解读、基于人工智能辅助信息整合实现深度精准诊断,以及基于HE染色图像的人工智能辅助患者生存和预后的准确预测。本文向读者展示了人工智能将助力开创的智能病理学的未来。