160 related articles for article (PubMed ID: 38003843)
1. Predicting Breast Cancer Risk Using Radiomics Features of Mammography Images.
Suzuki Y; Hanaoka S; Tanabe M; Yoshikawa T; Seto Y
J Pers Med; 2023 Oct; 13(11):. PubMed ID: 38003843
[TBL] [Abstract][Full Text] [Related]
2. Mammography-based radiomics for predicting the risk of breast cancer recurrence: a multicenter study.
Mao N; Yin P; Zhang H; Zhang K; Song X; Xing D; Chu T
Br J Radiol; 2021 Nov; 94(1127):20210348. PubMed ID: 34520235
[TBL] [Abstract][Full Text] [Related]
3. Predicting the Level of Tumor-Infiltrating Lymphocytes in Patients With Breast Cancer: Usefulness of Mammographic Radiomics Features.
Yu H; Meng X; Chen H; Liu J; Gao W; Du L; Chen Y; Wang Y; Liu X; Liu B; Fan J; Ma G
Front Oncol; 2021; 11():628577. PubMed ID: 33777776
[TBL] [Abstract][Full Text] [Related]
4. A multi-stage fusion framework to classify breast lesions using deep learning and radiomics features computed from four-view mammograms.
Jones MA; Sadeghipour N; Chen X; Islam W; Zheng B
Med Phys; 2023 Dec; 50(12):7670-7683. PubMed ID: 37083190
[TBL] [Abstract][Full Text] [Related]
5. Preoperative prediction of histologic grade in invasive breast cancer by using contrast-enhanced spectral mammography-based radiomics.
Mao N; Jiao Z; Duan S; Xu C; Xie H
J Xray Sci Technol; 2021; 29(5):763-772. PubMed ID: 34151880
[TBL] [Abstract][Full Text] [Related]
6. A Radiomics Study: Classification of Breast Lesions by Textural Features from Mammography Images.
Letchumanan N; Wong JHD; Tan LK; Ab Mumin N; Ng WL; Chan WY; Rahmat K
J Digit Imaging; 2023 Aug; 36(4):1533-1540. PubMed ID: 37253893
[TBL] [Abstract][Full Text] [Related]
7. Intratumoral and peritumoral radiomics for preoperative prediction of neoadjuvant chemotherapy effect in breast cancer based on contrast-enhanced spectral mammography.
Mao N; Shi Y; Lian C; Wang Z; Zhang K; Xie H; Zhang H; Chen Q; Cheng G; Xu C; Dai Y
Eur Radiol; 2022 May; 32(5):3207-3219. PubMed ID: 35066632
[TBL] [Abstract][Full Text] [Related]
8. Radiomics of contrast-enhanced spectral mammography for prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer.
Zhang K; Lin J; Lin F; Wang Z; Zhang H; Zhang S; Mao N; Qiao G
J Xray Sci Technol; 2023; 31(4):669-683. PubMed ID: 37066960
[TBL] [Abstract][Full Text] [Related]
9. Mammography-based radiomics nomogram: a potential biomarker to predict axillary lymph node metastasis in breast cancer.
Tan H; Wu Y; Bao F; Zhou J; Wan J; Tian J; Lin Y; Wang M
Br J Radiol; 2020 Jul; 93(1111):20191019. PubMed ID: 32401540
[TBL] [Abstract][Full Text] [Related]
10. Prediction of human epidermal growth factor receptor 2 (HER2) status in breast cancer by mammographic radiomics features and clinical characteristics: a multicenter study.
Deng Y; Lu Y; Li X; Zhu Y; Zhao Y; Ruan Z; Mei N; Yin B; Liu L
Eur Radiol; 2024 Jan; ():. PubMed ID: 38276982
[TBL] [Abstract][Full Text] [Related]
11. Improving the malignancy prediction of breast cancer based on the integration of radiomics features from dual-view mammography and clinical parameters.
Zhou C; Xie H; Zhu F; Yan W; Yu R; Wang Y
Clin Exp Med; 2023 Oct; 23(6):2357-2368. PubMed ID: 36413273
[TBL] [Abstract][Full Text] [Related]
12. Diagnostic performance of perilesional radiomics analysis of contrast-enhanced mammography for the differentiation of benign and malignant breast lesions.
Wang S; Sun Y; Li R; Mao N; Li Q; Jiang T; Chen Q; Duan S; Xie H; Gu Y
Eur Radiol; 2022 Jan; 32(1):639-649. PubMed ID: 34189600
[TBL] [Abstract][Full Text] [Related]
13. Intra- and peritumoral radiomics for predicting malignant BiRADS category 4 breast lesions on contrast-enhanced spectral mammography: a multicenter study.
Zhang S; Shao H; Li W; Zhang H; Lin F; Zhang Q; Zhang H; Wang Z; Gao J; Zhang R; Gu Y; Wang Y; Mao N; Xie H
Eur Radiol; 2023 Aug; 33(8):5411-5422. PubMed ID: 37014410
[TBL] [Abstract][Full Text] [Related]
14. Contrast-Enhanced Spectral Mammography-Based Prediction of Non-Sentinel Lymph Node Metastasis and Axillary Tumor Burden in Patients With Breast Cancer.
Wu X; Guo Y; Sa Y; Song Y; Li X; Lv Y; Xing D; Sun Y; Cong Y; Yu H; Jiang W
Front Oncol; 2022; 12():823897. PubMed ID: 35615151
[TBL] [Abstract][Full Text] [Related]
15. Prediction of radiation-induced acute skin toxicity in breast cancer patients using data encapsulation screening and dose-gradient-based multi-region radiomics technique: A multicenter study.
Feng H; Wang H; Xu L; Ren Y; Ni Q; Yang Z; Ma S; Deng Q; Chen X; Xia B; Kuang Y; Li X
Front Oncol; 2022; 12():1017435. PubMed ID: 36439515
[TBL] [Abstract][Full Text] [Related]
16. Radiomics Based on Digital Mammography Helps to Identify Mammographic Masses Suspicious for Cancer.
Wang G; Shi D; Guo Q; Zhang H; Wang S; Ren K
Front Oncol; 2022; 12():843436. PubMed ID: 35433437
[TBL] [Abstract][Full Text] [Related]
17. Application of mammography-based radiomics signature for preoperative prediction of triple-negative breast cancer.
Ge S; Yixing Y; Jia D; Ling Y
BMC Med Imaging; 2022 Sep; 22(1):166. PubMed ID: 36104679
[TBL] [Abstract][Full Text] [Related]
18. An MRI-based Radiomics Classifier for Preoperative Prediction of Ki-67 Status in Breast Cancer.
Liang C; Cheng Z; Huang Y; He L; Chen X; Ma Z; Huang X; Liang C; Liu Z
Acad Radiol; 2018 Sep; 25(9):1111-1117. PubMed ID: 29428211
[TBL] [Abstract][Full Text] [Related]
19. Intratumoral and peritumoral radiomics for preoperatively predicting the axillary non-sentinel lymph node metastasis in breast cancer on the basis of contrast-enhanced mammography: a multicenter study.
Lin F; Li Q; Wang Z; Shi Y; Ma H; Zhang H; Zhang K; Yang P; Zhang R; Duan S; Gu Y; Mao N; Xie H
Br J Radiol; 2023 Mar; 96(1143):20220068. PubMed ID: 36542866
[TBL] [Abstract][Full Text] [Related]
20. Evaluating the HER-2 status of breast cancer using mammography radiomics features.
Zhou J; Tan H; Bai Y; Li J; Lu Q; Chen R; Zhang M; Feng Q; Wang M
Eur J Radiol; 2019 Dec; 121():108718. PubMed ID: 31711023
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
