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

人工智能在癌症诊断和治疗中的新研究与未来展望。

Novel research and future prospects of artificial intelligence in cancer diagnosis and treatment.

机构信息

Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, No. 270 Dong'An Road, Shanghai, 200032, People's Republic of China.

Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, People's Republic of China.

出版信息

J Hematol Oncol. 2023 Nov 27;16(1):114. doi: 10.1186/s13045-023-01514-5.


DOI:10.1186/s13045-023-01514-5
PMID:38012673
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10680201/
Abstract

Research into the potential benefits of artificial intelligence for comprehending the intricate biology of cancer has grown as a result of the widespread use of deep learning and machine learning in the healthcare sector and the availability of highly specialized cancer datasets. Here, we review new artificial intelligence approaches and how they are being used in oncology. We describe how artificial intelligence might be used in the detection, prognosis, and administration of cancer treatments and introduce the use of the latest large language models such as ChatGPT in oncology clinics. We highlight artificial intelligence applications for omics data types, and we offer perspectives on how the various data types might be combined to create decision-support tools. We also evaluate the present constraints and challenges to applying artificial intelligence in precision oncology. Finally, we discuss how current challenges may be surmounted to make artificial intelligence useful in clinical settings in the future.

摘要

由于深度学习和机器学习在医疗保健领域的广泛应用以及高度专业化的癌症数据集的可用性,研究人工智能在理解癌症复杂生物学方面的潜在益处的工作已经增加。在这里,我们回顾了新的人工智能方法以及它们在肿瘤学中的应用。我们描述了人工智能如何用于癌症的检测、预后和治疗管理,并介绍了最新的大型语言模型(如 ChatGPT)在肿瘤学临床中的应用。我们强调了人工智能在组学数据类型中的应用,并提供了关于如何将各种数据类型结合起来创建决策支持工具的观点。我们还评估了目前在精准肿瘤学中应用人工智能的限制和挑战。最后,我们讨论了如何克服当前的挑战,以使人工智能在未来的临床环境中发挥作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f666/10680201/eb60f76aa229/13045_2023_1514_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f666/10680201/2df8f5c5ac02/13045_2023_1514_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f666/10680201/6640a7488c55/13045_2023_1514_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f666/10680201/e0e80828f535/13045_2023_1514_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f666/10680201/eb60f76aa229/13045_2023_1514_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f666/10680201/2df8f5c5ac02/13045_2023_1514_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f666/10680201/6640a7488c55/13045_2023_1514_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f666/10680201/e0e80828f535/13045_2023_1514_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f666/10680201/eb60f76aa229/13045_2023_1514_Fig4_HTML.jpg

相似文献

[1]
Novel research and future prospects of artificial intelligence in cancer diagnosis and treatment.

J Hematol Oncol. 2023-11-27

[2]
Artificial Intelligence for Precision Oncology.

Adv Exp Med Biol. 2022

[3]
Deep learning in cancer diagnosis, prognosis and treatment selection.

Genome Med. 2021-9-27

[4]
Artificial intelligence in oncology.

Cancer Sci. 2020-3-21

[5]
Precision Psychiatry Applications with Pharmacogenomics: Artificial Intelligence and Machine Learning Approaches.

Int J Mol Sci. 2020-2-1

[6]
Molecular-based precision oncology clinical decision making augmented by artificial intelligence.

Emerg Top Life Sci. 2021-12-21

[7]
Role of Machine Learning and Artificial Intelligence in Interventional Oncology.

Curr Oncol Rep. 2021-4-20

[8]
Artificial intelligence (AI) and machine learning (ML) in precision oncology: a review on enhancing discoverability through multiomics integration.

Br J Radiol. 2023-10

[9]
Applications of artificial intelligence multiomics in precision oncology.

J Cancer Res Clin Oncol. 2023-1

[10]
Artificial intelligence in cancer research, diagnosis and therapy.

Nat Rev Cancer. 2021-12

引用本文的文献

[1]
The SPINK Protein Family in Cancer: Emerging Roles in Tumor Progression, Therapeutic Resistance, and Precision Oncology.

Pharmaceuticals (Basel). 2025-8-13

[2]
A bibliometric analysis of large language model-based AI chatbots in surgery.

Ann Med Surg (Lond). 2025-5-12

[3]
The role of advanced diagnostics on precision medicine in hemato oncology.

Discov Oncol. 2025-8-11

[4]
Deep learning and radiomics fusion for predicting the invasiveness of lung adenocarcinoma within ground glass nodules.

Sci Rep. 2025-8-11

[5]
Proteomic alterations in ovarian cancer-Predicting residual disease status using artificial intelligence and SHAP-based biomarker interpretation.

Front Med (Lausanne). 2025-7-23

[6]
The application of random forest-based models in prognostication of gastrointestinal tract malignancies: a systematic review.

Front Artif Intell. 2025-7-18

[7]
Prognostic Significance of the Comprehensive Biomarker Analysis in Colorectal Cancer.

Life (Basel). 2025-7-14

[8]
Progress and current trends in prediction models for the occurrence and prognosis of cancer and cancer-related complications: a bibliometric and visualization analysis.

Front Oncol. 2025-7-8

[9]
Importance of landscape exploration and progress in molecular therapies and precision medicine for pancreatic ductal adenocarcinoma.

World J Gastrointest Oncol. 2025-7-15

[10]
Explainable machine learning model for predicting the transarterial chemoembolization response and subtypes of hepatocellular carcinoma patients.

BMC Gastroenterol. 2025-7-7

本文引用的文献

[1]
Classification of brain tumours from MRI images using deep learning-enabled hybrid optimization algorithm.

Network. 2023

[2]
AdvMIL: Adversarial multiple instance learning for the survival analysis on whole-slide images.

Med Image Anal. 2024-1

[3]
A deep-learning approach for segmentation of liver tumors in magnetic resonance imaging using UNet+.

BMC Cancer. 2023-11-3

[4]
Advances in medical image analysis with vision Transformers: A comprehensive review.

Med Image Anal. 2024-1

[5]
Teaching AI Ethics in Medical Education: A Scoping Review of Current Literature and Practices.

Perspect Med Educ. 2023

[6]
Ultra-fast deep-learned CNS tumour classification during surgery.

Nature. 2023-10

[7]
TransU²-Net: An Effective Medical Image Segmentation Framework Based on Transformer and U²-Net.

IEEE J Transl Eng Health Med. 2023

[8]
Classification of cancer cells at the sub-cellular level by phonon microscopy using deep learning.

Sci Rep. 2023-9-27

[9]
A CNN-based approach for joint segmentation and quantification of nuclei and NORs in AgNOR-stained images.

Comput Methods Programs Biomed. 2023-12

[10]
SiGra: single-cell spatial elucidation through an image-augmented graph transformer.

Nat Commun. 2023-9-12

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