210 related articles for article (PubMed ID: 35463368)
1. Dual-Branch Convolutional Neural Network Based on Ultrasound Imaging in the Early Prediction of Neoadjuvant Chemotherapy Response in Patients With Locally Advanced Breast Cancer.
Xie J; Shi H; Du C; Song X; Wei J; Dong Q; Wan C
Front Oncol; 2022; 12():812463. PubMed ID: 35463368
[TBL] [Abstract][Full Text] [Related]
2. Prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer using a deep learning (DL) method.
Qu YH; Zhu HT; Cao K; Li XT; Ye M; Sun YS
Thorac Cancer; 2020 Mar; 11(3):651-658. PubMed ID: 31944571
[TBL] [Abstract][Full Text] [Related]
3. Role of the Intravoxel Incoherent Motion Diffusion Weighted Imaging in the Pre-treatment Prediction and Early Response Monitoring to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer.
Che S; Zhao X; Ou Y; Li J; Wang M; Wu B; Zhou C
Medicine (Baltimore); 2016 Jan; 95(4):e2420. PubMed ID: 26825883
[TBL] [Abstract][Full Text] [Related]
4. Pretreatment ultrasound-based deep learning radiomics model for the early prediction of pathologic response to neoadjuvant chemotherapy in breast cancer.
Yu FH; Miao SM; Li CY; Hang J; Deng J; Ye XH; Liu Y
Eur Radiol; 2023 Aug; 33(8):5634-5644. PubMed ID: 36976336
[TBL] [Abstract][Full Text] [Related]
5. The Value of 18F-FDG PET/CT Imaging Combined With Pretherapeutic Ki67 for Early Prediction of Pathologic Response After Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer.
Luo J; Zhou Z; Yang Z; Chen X; Cheng J; Shao Z; Guo X; Tuan J; Fu X; Yu X
Medicine (Baltimore); 2016 Feb; 95(8):e2914. PubMed ID: 26937935
[TBL] [Abstract][Full Text] [Related]
6. Transfer learning of pre-treatment quantitative ultrasound multi-parametric images for the prediction of breast cancer response to neoadjuvant chemotherapy.
Falou O; Sannachi L; Haque M; Czarnota GJ; Kolios MC
Sci Rep; 2024 Jan; 14(1):2340. PubMed ID: 38282158
[TBL] [Abstract][Full Text] [Related]
7. Multiparametric Contrast-Enhanced Ultrasound in Early Prediction of Response to Neoadjuvant Chemotherapy and Recurrence-Free Survival in Breast Cancer.
Wan C; Zhou L; Li H; Wang L; Li F; Yin W; Wang Y; Jiang L; Lu J
Diagnostics (Basel); 2023 Jul; 13(14):. PubMed ID: 37510121
[TBL] [Abstract][Full Text] [Related]
8. Multi-input deep learning architecture for predicting breast tumor response to chemotherapy using quantitative MR images.
El Adoui M; Drisis S; Benjelloun M
Int J Comput Assist Radiol Surg; 2020 Sep; 15(9):1491-1500. PubMed ID: 32556920
[TBL] [Abstract][Full Text] [Related]
9. Prediction of response to neoadjuvant chemotherapy in breast cancer with recurrent neural networks and raw ultrasound signals.
Byra M; Dobruch-Sobczak K; Piotrzkowska-Wroblewska H; Klimonda Z; Litniewski J
Phys Med Biol; 2022 Sep; 67(18):. PubMed ID: 36001984
[No Abstract] [Full Text] [Related]
10. A hierarchical self-attention-guided deep learning framework to predict breast cancer response to chemotherapy using pre-treatment tumor biopsies.
Saednia K; Tran WT; Sadeghi-Naini A
Med Phys; 2023 Dec; 50(12):7852-7864. PubMed ID: 37403567
[TBL] [Abstract][Full Text] [Related]
11. Strain ultrasonic elastography imaging features of locally advanced breast cancer: association with response to neoadjuvant chemotherapy and recurrence-free survival.
Wan C; Zhou L; Jin Y; Li F; Wang L; Yin W; Wang Y; Li H; Jiang L; Lu J
BMC Med Imaging; 2023 Dec; 23(1):216. PubMed ID: 38129778
[TBL] [Abstract][Full Text] [Related]
12. Apriori prediction of chemotherapy response in locally advanced breast cancer patients using CT imaging and deep learning: transformer versus transfer learning.
Moslemi A; Osapoetra LO; Dasgupta A; Alberico D; Trudeau M; Gandhi S; Eisen A; Wright F; Look-Hong N; Curpen B; Kolios MC; Czarnota GJ
Front Oncol; 2024; 14():1359148. PubMed ID: 38756659
[TBL] [Abstract][Full Text] [Related]
13. An integrated deep learning model for the prediction of pathological complete response to neoadjuvant chemotherapy with serial ultrasonography in breast cancer patients: a multicentre, retrospective study.
Wu L; Ye W; Liu Y; Chen D; Wang Y; Cui Y; Li Z; Li P; Li Z; Liu Z; Liu M; Liang C; Yang X; Xie Y; Wang Y
Breast Cancer Res; 2022 Nov; 24(1):81. PubMed ID: 36414984
[TBL] [Abstract][Full Text] [Related]
14. Deep Learning of Multimodal Ultrasound: Stratifying the Response to Neoadjuvant Chemotherapy in Breast Cancer Before Treatment.
Gu J; Zhong X; Fang C; Lou W; Fu P; Woodruff HC; Wang B; Jiang T; Lambin P
Oncologist; 2024 Feb; 29(2):e187-e197. PubMed ID: 37669223
[TBL] [Abstract][Full Text] [Related]
15. Deep learning radiomic analysis of DCE-MRI combined with clinical characteristics predicts pathological complete response to neoadjuvant chemotherapy in breast cancer.
Li Y; Fan Y; Xu D; Li Y; Zhong Z; Pan H; Huang B; Xie X; Yang Y; Liu B
Front Oncol; 2022; 12():1041142. PubMed ID: 36686755
[TBL] [Abstract][Full Text] [Related]
16. Deep Learning Model Based on Dual-Modal Ultrasound and Molecular Data for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer.
Huang JX; Shi J; Ding SS; Zhang HL; Wang XY; Lin SY; Xu YF; Wei MJ; Liu LZ; Pei XQ
Acad Radiol; 2023 Sep; 30 Suppl 2():S50-S61. PubMed ID: 37270368
[TBL] [Abstract][Full Text] [Related]
17. Prediction of pathological complete response of breast cancer patients who received neoadjuvant chemotherapy with a nomogram based on clinicopathologic variables, ultrasound, and MRI.
Zhang MQ; Liu XP; Du Y; Zha HL; Zha XM; Wang J; Liu XA; Wang SJ; Zou QG; Zhang JL; Li CY
Br J Radiol; 2024 Jan; 97(1153):228-236. PubMed ID: 38263817
[TBL] [Abstract][Full Text] [Related]
18. Early prediction of treatment response to neoadjuvant chemotherapy based on longitudinal ultrasound images of HER2-positive breast cancer patients by Siamese multi-task network: A multicentre, retrospective cohort study.
Liu Y; Wang Y; Wang Y; Xie Y; Cui Y; Feng S; Yao M; Qiu B; Shen W; Chen D; Du G; Chen X; Liu Z; Li Z; Yang X; Liang C; Wu L
EClinicalMedicine; 2022 Oct; 52():101562. PubMed ID: 35928032
[TBL] [Abstract][Full Text] [Related]
19. Ultrasound-based deep learning radiomics in the assessment of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer.
Jiang M; Li CL; Luo XM; Chuan ZR; Lv WZ; Li X; Cui XW; Dietrich CF
Eur J Cancer; 2021 Apr; 147():95-105. PubMed ID: 33639324
[TBL] [Abstract][Full Text] [Related]
20. Deep learning of quantitative ultrasound multi-parametric images at pre-treatment to predict breast cancer response to chemotherapy.
Taleghamar H; Jalalifar SA; Czarnota GJ; Sadeghi-Naini A
Sci Rep; 2022 Feb; 12(1):2244. PubMed ID: 35145158
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
