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步宏. 人工智能推动精准病理诊断的发展[J]. 四川大学学报(医学版), 2021, 52(2): 153-155. DOI: 10.12182/20210360206
引用本文: 步宏. 人工智能推动精准病理诊断的发展[J]. 四川大学学报(医学版), 2021, 52(2): 153-155. DOI: 10.12182/20210360206
BU Hong. New Trends of Development in Precision Pathological Diagnosis Promoted by Artificial Intelligence[J]. Journal of Sichuan University (Medical Sciences), 2021, 52(2): 153-155. DOI: 10.12182/20210360206
Citation: BU Hong. New Trends of Development in Precision Pathological Diagnosis Promoted by Artificial Intelligence[J]. Journal of Sichuan University (Medical Sciences), 2021, 52(2): 153-155. DOI: 10.12182/20210360206

人工智能推动精准病理诊断的发展

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

  • 摘要: 病理诊断在精准医学中扮演着非常重要的角色,无论是病理医生资源有限的现实,还是不断精细量化的临床诊断需求,都对精准的病理诊断能力提出了更高的挑战。医学界希望人工智能(artificial intelligence, AI)成为从多个方面解决这一难题的得力助手。本文讨论了AI推动精准病理诊断的几个方面:AI辅助病变组织的精准获取、AI辅助组织病理精准诊断、AI辅助组织学分级和定量评分、AI辅助肿瘤生物标记物的精准评估、AI辅助基于HE图像预测分子特征和精准的生物信息解读、AI辅助信息整合实现深层次的精准诊断、AI辅助基于HE图像精准预测患者的生存和预后,为读者展现AI技术为我们迎来的智慧病理的明天。

     

    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.

     

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