文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

智能肿瘤学:人工智能与肿瘤学的融合。

Intelligent oncology: The convergence of artificial intelligence and oncology.

作者信息

Lin Bo, Tan Zhibo, Mo Yaqi, Yang Xue, Liu Yajie, Xu Bo

机构信息

Chongqing Key Laboratory of Intelligent Oncology for Breast Cancer, Chongqing University Cancer Hospital and Chongqing University School of Medicine, Institute of Intelligent Oncology, Chongqing University, China.

Department of Radiation Oncology, Peking University Shenzhen Hospital, Department of Radiation Oncology, Peking University Shenzhen Hospital, Shenzhen, China.

出版信息

J Natl Cancer Cent. 2022 Dec 5;3(1):83-91. doi: 10.1016/j.jncc.2022.11.004. eCollection 2023 Mar.


DOI:10.1016/j.jncc.2022.11.004
PMID:39036310
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11256531/
Abstract

With increasingly explored ideologies and technologies for potential applications of artificial intelligence (AI) in oncology, we here describe a holistic and structured concept termed intelligent oncology. Intelligent oncology is defined as a cross-disciplinary specialty which integrates oncology, radiology, pathology, molecular biology, multi-omics and computer sciences, aiming to promote cancer prevention, screening, early diagnosis and precision treatment. The development of intelligent oncology has been facilitated by fast AI technology development such as natural language processing, machine/deep learning, computer vision, and robotic process automation. While the concept and applications of intelligent oncology is still in its infancy, and there are still many hurdles and challenges, we are optimistic that it will play a pivotal role for the future of basic, translational and clinical oncology.

摘要

随着人工智能(AI)在肿瘤学潜在应用方面的意识形态和技术得到越来越多的探索,我们在此描述一个称为智能肿瘤学的整体且结构化的概念。智能肿瘤学被定义为一门跨学科专业,它整合了肿瘤学、放射学、病理学、分子生物学、多组学和计算机科学,旨在促进癌症预防、筛查、早期诊断和精准治疗。自然语言处理、机器/深度学习、计算机视觉和机器人流程自动化等快速发展的人工智能技术推动了智能肿瘤学的发展。虽然智能肿瘤学的概念和应用仍处于起步阶段,并且仍然存在许多障碍和挑战,但我们乐观地认为它将对基础、转化和临床肿瘤学的未来发挥关键作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/475d/11256531/87978f71f293/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/475d/11256531/e2a06c8011d2/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/475d/11256531/341dc8d3c0d2/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/475d/11256531/87978f71f293/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/475d/11256531/e2a06c8011d2/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/475d/11256531/341dc8d3c0d2/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/475d/11256531/87978f71f293/gr3.jpg

相似文献

[1]
Intelligent oncology: The convergence of artificial intelligence and oncology.

J Natl Cancer Cent. 2022-12-5

[2]
Artificial intelligence and hybrid imaging: the best match for personalized medicine in oncology.

Eur J Hybrid Imaging. 2020-12-9

[3]
Artificial intelligence technologies and compassion in healthcare: A systematic scoping review.

Front Psychol. 2023-1-17

[4]
Artificial Intelligence for Precision Oncology.

Adv Exp Med Biol. 2022

[5]
Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine.

Cancers (Basel). 2020-11-26

[6]
Artificial intelligence in radiation oncology: A specialty-wide disruptive transformation?

Radiother Oncol. 2018-6-12

[7]
Artificial intelligence in oncology.

Cancer Sci. 2020-3-21

[8]
Research and application of omics and artificial intelligence in cancer.

Phys Med Biol. 2024-10-18

[9]
Artificial intelligence and machine learning for medical imaging: A technology review.

Phys Med. 2021-3

[10]
The use of artificial intelligence, machine learning and deep learning in oncologic histopathology.

J Oral Pathol Med. 2020-6-15

引用本文的文献

[1]
Ferroptosis and Nrf2 Signaling in Head and Neck Cancer: Resistance Mechanisms and Therapeutic Prospects.

Antioxidants (Basel). 2025-8-13

[2]
Decoding the tumor microenvironment: insights into immunotherapy and beyond.

J Natl Cancer Cent. 2025-4-28

[3]
Artificial intelligence-assisted delineation for postoperative radiotherapy in patients with lung cancer: a prospective, multi-center, cohort study.

Front Oncol. 2024-10-22

[4]
An interpretable deep learning model for detecting pathogenic variants of breast cancer from hematoxylin and eosin-stained pathological images.

PeerJ. 2024

[5]
Deep Learning for MRI Segmentation and Molecular Subtyping in Glioblastoma: Critical Aspects from an Emerging Field.

Biomedicines. 2024-8-16

[6]
Theranostic digital twins: Concept, framework and roadmap towards personalized radiopharmaceutical therapies.

Theranostics. 2024

[7]
Chinese Oncologists' Perspectives on Integrating AI into Clinical Practice: Cross-Sectional Survey Study.

JMIR Form Res. 2024-6-5

[8]
The Use of Artificial Intelligence in Head and Neck Cancers: A Multidisciplinary Survey.

J Pers Med. 2024-3-25

[9]
Navigating Glioblastoma Diagnosis and Care: Transformative Pathway of Artificial Intelligence in Integrative Oncology.

Cureus. 2023-8-27

[10]
A multi-class classification algorithm based on hematoxylin-eosin staining for neoadjuvant therapy in rectal cancer: a retrospective study.

PeerJ. 2023

本文引用的文献

[1]
One-step algorithm for fast-track localization and multi-category classification of histological subtypes in lung cancer.

Eur J Radiol. 2022-9

[2]
A Deep Learning Model for Cervical Cancer Screening on Liquid-Based Cytology Specimens in Whole Slide Images.

Cancers (Basel). 2022-2-24

[3]
Uncovering interpretable potential confounders in electronic medical records.

Nat Commun. 2022-2-23

[4]
Effect of Artificial Intelligence Tutoring vs Expert Instruction on Learning Simulated Surgical Skills Among Medical Students: A Randomized Clinical Trial.

JAMA Netw Open. 2022-2-1

[5]
A Survey on Vision Transformer.

IEEE Trans Pattern Anal Mach Intell. 2023-1

[6]
Outstanding negative prediction performance of solid pulmonary nodule volume AI for ultra-LDCT baseline lung cancer screening risk stratification.

Lung Cancer. 2022-3

[7]
Deep learning links histology, molecular signatures and prognosis in cancer.

Nat Cancer. 2020-8

[8]
AI in health and medicine.

Nat Med. 2022-1

[9]
Development and validation of a radiopathomics model to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicentre observational study.

Lancet Digit Health. 2022-1

[10]
Predicting Post-Therapeutic Visual Acuity and OCT Images in Patients With Central Serous Chorioretinopathy by Artificial Intelligence.

Front Bioeng Biotechnol. 2021-11-23

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索