• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
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
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
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 @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

Recent Innovative Machine Learning-Based Techniques for Breast Cancer Diagnosis and Treatment.

作者信息

Mahmoud Ali, Ghazal Mohammed, El-Baz Ayman

机构信息

Bioengineering Department, J.B. Speed School of Engineering, University of Louisville, Louisville, KY 40292, USA.

Electrical, Computer, and Biomedical Engineering Department, Abu Dhabi University, Abu Dhabi, UAE.

出版信息

Technol Cancer Res Treat. 2024 Jan-Dec;23:15330338241298854. doi: 10.1177/15330338241298854.

DOI:10.1177/15330338241298854
PMID:39544092
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11565613/
Abstract
摘要

相似文献

1
Recent Innovative Machine Learning-Based Techniques for Breast Cancer Diagnosis and Treatment.近期基于机器学习的乳腺癌诊断与治疗创新技术
Technol Cancer Res Treat. 2024 Jan-Dec;23:15330338241298854. doi: 10.1177/15330338241298854.
2
Prediction and Diagnosis of Breast Cancer Using Machine and Modern Deep Learning Models.使用机器和现代深度学习模型预测和诊断乳腺癌。
Asian Pac J Cancer Prev. 2024 Mar 1;25(3):1077-1085. doi: 10.31557/APJCP.2024.25.3.1077.
3
PSOWNNs-CNN: A Computational Radiology for Breast Cancer Diagnosis Improvement Based on Image Processing Using Machine Learning Methods.PSOWNNs-CNN：一种基于图像处理和机器学习方法的计算机放射学乳腺癌诊断改进算法。
Comput Intell Neurosci. 2022 May 11;2022:5667264. doi: 10.1155/2022/5667264. eCollection 2022.
4
A Comparative Analysis of Breast Cancer Detection and Diagnosis Using Data Visualization and Machine Learning Applications.使用数据可视化和机器学习应用对乳腺癌检测与诊断的比较分析
Healthcare (Basel). 2020 Apr 26;8(2):111. doi: 10.3390/healthcare8020111.
5
Machine learning and deep learning techniques for breast cancer diagnosis and classification: a comprehensive review of medical imaging studies.用于乳腺癌诊断和分类的机器学习与深度学习技术：医学影像研究综述
J Cancer Res Clin Oncol. 2023 Sep;149(12):10473-10491. doi: 10.1007/s00432-023-04956-z. Epub 2023 Jun 6.
6
Machine learning models in breast cancer survival prediction.用于乳腺癌生存预测的机器学习模型。
Technol Health Care. 2016;24(1):31-42. doi: 10.3233/THC-151071.
7
Recent advancements in machine learning and deep learning-based breast cancer detection using mammograms.基于机器学习和深度学习的乳腺 X 线摄影乳腺癌检测的最新进展。
Phys Med. 2023 Oct;114:103138. doi: 10.1016/j.ejmp.2023.103138. Epub 2023 Sep 28.
8
The BCPM method: decoding breast cancer with machine learning.BCPM 方法：用机器学习解码乳腺癌。
BMC Med Imaging. 2024 Sep 17;24(1):248. doi: 10.1186/s12880-024-01402-5.
9
Recent advancement in cancer diagnosis using machine learning and deep learning techniques: A comprehensive review.利用机器学习和深度学习技术进行癌症诊断的最新进展：全面综述。
Comput Biol Med. 2022 Jul;146:105580. doi: 10.1016/j.compbiomed.2022.105580. Epub 2022 May 5.
10
Application of machine learning in the analysis of multiparametric MRI data for the differentiation of treatment responses in breast cancer: retrospective study.机器学习在多参数MRI数据分析中用于区分乳腺癌治疗反应的应用：回顾性研究
Eur J Cancer Prev. 2025 Jan 1;34(1):56-65. doi: 10.1097/CEJ.0000000000000892. Epub 2024 Jun 19.

本文引用的文献

1
A Beam Angle Selection Method to Improve Plan Robustness Against Position Error in Intensity-Modulated Radiotherapy for Left-Sided Breast Cancer.一种用于改善左侧乳腺癌调强放疗中位置误差的计划稳健性的射束角度选择方法。
Technol Cancer Res Treat. 2024 Jan-Dec;23:15330338241259633. doi: 10.1177/15330338241259633.
2
Quantify the Effect of Air Gap Errors on Skin Dose for Breast Cancer Radiotherapy.量化空气间隙误差对乳腺癌放射治疗皮肤剂量的影响。
Technol Cancer Res Treat. 2024 Jan-Dec;23:15330338241258566. doi: 10.1177/15330338241258566.
3
Noninvasive Assessment of Tumor Histological Grade in Invasive Breast Carcinoma Based on Ultrasound Radiomics and Clinical Characteristics: A Multicenter Study.基于超声放射组学和临床特征的浸润性乳腺癌肿瘤组织学分级的无创评估：一项多中心研究。
Technol Cancer Res Treat. 2024 Jan-Dec;23:15330338241257424. doi: 10.1177/15330338241257424.
4
Calcium-sensing Receptor, a Potential Biomarker Revealed by Large-scale Public Databases and Experimental Verification in Metastatic Breast Cancer.钙敏感受体：大规模公共数据库揭示的潜在生物标志物，并在转移性乳腺癌中得到实验验证。
Technol Cancer Res Treat. 2024 Jan-Dec;23:15330338241254219. doi: 10.1177/15330338241254219.
5
Identification of Breast Cancer Subtypes Based on Endoplasmic Reticulum Stress-Related Genes and Analysis of Prognosis and Immune Microenvironment in Breast Cancer Patients.基于内质网应激相关基因的乳腺癌亚型鉴定及乳腺癌患者预后和免疫微环境分析。
Technol Cancer Res Treat. 2024 Jan-Dec;23:15330338241241484. doi: 10.1177/15330338241241484.
6
Breast Cancer Prediction Based on Multiple Machine Learning Algorithms.基于多种机器学习算法的乳腺癌预测。
Technol Cancer Res Treat. 2024 Jan-Dec;23:15330338241234791. doi: 10.1177/15330338241234791.
7
Determination of and Effects of Taxifolin and Epirubicin on Epithelial-Mesenchymal Transition in Mouse Breast Cancer Cells.二氢槲皮素和表阿霉素对小鼠乳腺癌细胞上皮-间质转化的影响及其机制研究。
Technol Cancer Res Treat. 2024 Jan-Dec;23:15330338241241245. doi: 10.1177/15330338241241245.
8
Decanoylcarnitine Inhibits Triple-Negative Breast Cancer Progression via Mmp9 in an Intermittent Fasting Obesity Mouse.癸酰基肉碱通过 MMP9 抑制间歇性禁食肥胖小鼠的三阴性乳腺癌进展。
Technol Cancer Res Treat. 2024 Jan-Dec;23:15330338241233443. doi: 10.1177/15330338241233443.
9
Randomized Pilot Study of a Keratin-based Topical Cream for Radiation Dermatitis in Breast Cancer Patients.随机试点研究：一种基于角蛋白的局部乳膏治疗乳腺癌患者放射性皮炎。
Technol Cancer Res Treat. 2024 Jan-Dec;23:15330338231222137. doi: 10.1177/15330338231222137.
10
Histological Grade and Immunohistochemical Biomarkers of Breast Cancer: Correlation to Ultrasound Features.乳腺癌的组织学分级和免疫组化生物标志物：与超声特征的相关性
J Ultrasound Med. 2017 Sep;36(9):1883-1894. doi: 10.1002/jum.14247. Epub 2017 May 27.