BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

355 related articles for article (PubMed ID: 35198437)

  • 1. Treatment Response Prediction Using Ultrasound-Based Pre-, Post-Early, and Delta Radiomics in Neoadjuvant Chemotherapy in Breast Cancer.
    Yang M; Liu H; Dai Q; Yao L; Zhang S; Wang Z; Li J; Duan Q
    Front Oncol; 2022; 12():748008. PubMed ID: 35198437
    [TBL] [Abstract][Full Text] [Related]  

  • 2. An ultrasound-based nomogram model in the assessment of pathological complete response of neoadjuvant chemotherapy in breast cancer.
    Liu J; Leng X; Liu W; Ma Y; Qiu L; Zumureti T; Zhang H; Mila Y
    Front Oncol; 2024; 14():1285511. PubMed ID: 38500656
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. 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]  

  • 5. Construction and validation of a personalized nomogram of ultrasound for pretreatment prediction of breast cancer patients sensitive to neoadjuvant chemotherapy.
    Zhang MQ; Du Y; Zha HL; Liu XP; Cai MJ; Chen ZH; Chen R; Wang J; Wang SJ; Zhang JL; Li CY
    Br J Radiol; 2022 Dec; 95(1140):20220626. PubMed ID: 36378247
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Delta-Radiomics Based on Dynamic Contrast-Enhanced MRI Predicts Pathologic Complete Response in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy.
    Guo L; Du S; Gao S; Zhao R; Huang G; Jin F; Teng Y; Zhang L
    Cancers (Basel); 2022 Jul; 14(14):. PubMed ID: 35884576
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Ultrasound radiomics-based nomogram to predict lymphovascular invasion in invasive breast cancer: a multicenter, retrospective study.
    Du Y; Cai M; Zha H; Chen B; Gu J; Zhang M; Liu W; Liu X; Liu X; Zong M; Li C
    Eur Radiol; 2024 Jan; 34(1):136-148. PubMed ID: 37518678
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Development of an ultrasound-based radiomics nomogram to preoperatively predict Ki-67 expression level in patients with breast cancer.
    Liu J; Wang X; Hu M; Zheng Y; Zhu L; Wang W; Hu J; Zhou Z; Dai Y; Dong F
    Front Oncol; 2022; 12():963925. PubMed ID: 36046035
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Machine Learning-Based Radiomics Nomogram Using Magnetic Resonance Images for Prediction of Neoadjuvant Chemotherapy Efficacy in Breast Cancer Patients.
    Chen S; Shu Z; Li Y; Chen B; Tang L; Mo W; Shao G; Shao F
    Front Oncol; 2020; 10():1410. PubMed ID: 32923392
    [No Abstract]   [Full Text] [Related]  

  • 10. Prediction of response to neoadjuvant chemotherapy in advanced gastric cancer: A radiomics nomogram analysis based on CT images and clinicopathological features.
    Tan X; Yang X; Hu S; Ge Y; Wu Q; Wang J; Sun Z
    J Xray Sci Technol; 2023; 31(1):49-61. PubMed ID: 36314190
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Radiomics Based on Dynamic Contrast-Enhanced MRI to Early Predict Pathologic Complete Response in Breast Cancer Patients Treated with Neoadjuvant Therapy.
    Zeng Q; Ke M; Zhong L; Zhou Y; Zhu X; He C; Liu L
    Acad Radiol; 2023 Aug; 30(8):1638-1647. PubMed ID: 36564256
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A nomogram model based on pre-treatment and post-treatment MR imaging radiomics signatures: application to predict progression-free survival for nasopharyngeal carcinoma.
    Sun MX; Zhao MJ; Zhao LH; Jiang HR; Duan YX; Li G
    Radiat Oncol; 2023 Apr; 18(1):67. PubMed ID: 37041545
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A Delta-radiomics model for preoperative evaluation of Neoadjuvant chemotherapy response in high-grade osteosarcoma.
    Lin P; Yang PF; Chen S; Shao YY; Xu L; Wu Y; Teng W; Zhou XZ; Li BH; Luo C; Xu LM; Huang M; Niu TY; Ye ZM
    Cancer Imaging; 2020 Jan; 20(1):7. PubMed ID: 31937372
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Contrast-Enhanced Spectral Mammography-Based Radiomics Nomogram for the Prediction of Neoadjuvant Chemotherapy-Insensitive Breast Cancers.
    Wang Z; Lin F; Ma H; Shi Y; Dong J; Yang P; Zhang K; Guo N; Zhang R; Cui J; Duan S; Mao N; Xie H
    Front Oncol; 2021; 11():605230. PubMed ID: 33692950
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Computed Tomography-Based Radiomics Analysis for Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer Patients.
    Duan Y; Yang G; Miao W; Song B; Wang Y; Yan L; Wu F; Zhang R; Mao Y; Wang Z
    J Comput Assist Tomogr; 2023 Mar-Apr 01; 47(2):199-204. PubMed ID: 36790871
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Integration of ultrasound radiomics features and clinical factors: A nomogram model for identifying the Ki-67 status in patients with breast carcinoma.
    Wu J; Fang Q; Yao J; Ge L; Hu L; Wang Z; Jin G
    Front Oncol; 2022; 12():979358. PubMed ID: 36276108
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A delta-radiomic lymph node model using dynamic contrast enhanced MRI for the early prediction of axillary response after neoadjuvant chemotherapy in breast cancer patients.
    Liu S; Du S; Gao S; Teng Y; Jin F; Zhang L
    BMC Cancer; 2023 Jan; 23(1):15. PubMed ID: 36604679
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Intratumoral and Peritumoral Analysis of Mammography, Tomosynthesis, and Multiparametric MRI for Predicting Ki-67 Level in Breast Cancer: a Radiomics-Based Study.
    Jiang T; Song J; Wang X; Niu S; Zhao N; Dong Y; Wang X; Luo Y; Jiang X
    Mol Imaging Biol; 2022 Aug; 24(4):550-559. PubMed ID: 34904187
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Prediction of Ki-67 of Invasive Ductal Breast Cancer Based on Ultrasound Radiomics Nomogram.
    Zhu Y; Dou Y; Qin L; Wang H; Wen Z
    J Ultrasound Med; 2023 Feb; 42(3):649-664. PubMed ID: 35851691
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 18.