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Performance of radiomics models for tumour-infiltrating lymphocyte (TIL) prediction in breast cancer: the role of the dynamic contrast-enhanced (DCE) MRI phase.用于乳腺癌中肿瘤浸润淋巴细胞（TIL）预测的放射组学模型的性能：动态对比增强（DCE）MRI相位的作用
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Radiomics Analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Prediction of Sentinel Lymph Node Metastasis in Breast Cancer.动态对比增强磁共振成像的影像组学分析用于预测乳腺癌前哨淋巴结转移
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Radiomics in breast MRI: current progress toward clinical application in the era of artificial intelligence.乳腺 MRI 的放射组学：人工智能时代向临床应用的当前进展。
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Independent validation of machine learning in diagnosing breast Cancer on magnetic resonance imaging within a single institution.在单家医疗机构内使用机器学习对乳腺磁共振成像进行独立验证诊断乳腺癌。
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Radiomics Based on Multimodal MRI for the Differential Diagnosis of Benign and Malignant Breast Lesions.基于多模态磁共振成像的影像组学用于乳腺良恶性病变的鉴别诊断
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AI-enhanced simultaneous multiparametric F-FDG PET/MRI for accurate breast cancer diagnosis.人工智能增强的同步多参数 F-FDG PET/MRI 用于准确诊断乳腺癌。
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Radiomics and Machine Learning with Multiparametric Breast MRI for Improved Diagnostic Accuracy in Breast Cancer Diagnosis.基于多参数乳腺MRI的影像组学与机器学习提高乳腺癌诊断的准确性
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本文引用的文献
1
AI-Enhanced PET and MR Imaging for Patients with Breast Cancer.人工智能增强的乳腺癌患者 PET 和 MR 成像
PET Clin. 2023 Oct;18(4):567-575. doi: 10.1016/j.cpet.2023.05.002. Epub 2023 Jun 17.
2
Oncologic Imaging and Radiomics: A Walkthrough Review of Methodological Challenges.肿瘤影像学与放射组学：方法学挑战的概述性综述
Cancers (Basel). 2022 Oct 5;14(19):4871. doi: 10.3390/cancers14194871.
3
A Simultaneous Multiparametric F-FDG PET/MRI Radiomics Model for the Diagnosis of Triple Negative Breast Cancer.一种用于诊断三阴性乳腺癌的同时多参数F-FDG PET/MRI影像组学模型。
Cancers (Basel). 2022 Aug 16;14(16):3944. doi: 10.3390/cancers14163944.
4
Is Artificial Intelligence (AI) a Pipe Dream? Why Legal Issues Present Significant Hurdles to AI Autonomy.人工智能（AI）是否只是一场白日梦？法律问题为何成为 AI 自主化的重大障碍。
AJR Am J Roentgenol. 2022 Jul;219(1):152-156. doi: 10.2214/AJR.21.27224. Epub 2022 Feb 9.
5
Radiomics and Artificial Intelligence for Biomarker and Prediction Model Development in Oncology.肿瘤学中用于生物标志物和预测模型开发的放射组学与人工智能
Comput Struct Biotechnol J. 2019 Jul 12;17:995-1008. doi: 10.1016/j.csbj.2019.07.001. eCollection 2019.
6
How clinical imaging can assess cancer biology.临床影像学如何评估癌症生物学。
Insights Imaging. 2019 Mar 4;10(1):28. doi: 10.1186/s13244-019-0703-0.
7
Making Molecular Imaging a Clinical Tool for Precision Oncology: A Review.将分子影像学转化为精准肿瘤学的临床工具：综述。
JAMA Oncol. 2017 May 1;3(5):695-701. doi: 10.1001/jamaoncol.2016.5084.
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