These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

738 related articles for article (PubMed ID: 34295877)

  • 1. Prediction of Tumor Shrinkage Pattern to Neoadjuvant Chemotherapy Using a Multiparametric MRI-Based Machine Learning Model in Patients With Breast Cancer.
    Huang Y; Chen W; Zhang X; He S; Shao N; Shi H; Lin Z; Wu X; Li T; Lin H; Lin Y
    Front Bioeng Biotechnol; 2021; 9():662749. PubMed ID: 34295877
    [No Abstract]   [Full Text] [Related]  

  • 2. Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.
    Huang Y; Wei L; Hu Y; Shao N; Lin Y; He S; Shi H; Zhang X; Lin Y
    Front Oncol; 2021; 11():706733. PubMed ID: 34490107
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Impact of Machine Learning With Multiparametric Magnetic Resonance Imaging of the Breast for Early Prediction of Response to Neoadjuvant Chemotherapy and Survival Outcomes in Breast Cancer Patients.
    Tahmassebi A; Wengert GJ; Helbich TH; Bago-Horvath Z; Alaei S; Bartsch R; Dubsky P; Baltzer P; Clauser P; Kapetas P; Morris EA; Meyer-Baese A; Pinker K
    Invest Radiol; 2019 Feb; 54(2):110-117. PubMed ID: 30358693
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Multiparametric MRI radiomics fusion for predicting the response and shrinkage pattern to neoadjuvant chemotherapy in breast cancer.
    Fan M; Wu X; Yu J; Liu Y; Wang K; Xue T; Zeng T; Chen S; Li L
    Front Oncol; 2023; 13():1057841. PubMed ID: 37207135
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.
    Wang X; Wan Q; Chen H; Li Y; Li X
    Eur Radiol; 2020 Aug; 30(8):4595-4605. PubMed ID: 32222795
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Discrimination between HER2-overexpressing, -low-expressing, and -zero-expressing statuses in breast cancer using multiparametric MRI-based radiomics.
    Zheng S; Yang Z; Du G; Zhang Y; Jiang C; Xu T; Li B; Wang D; Qiu Y; Lin D; Zhang X; Shen J
    Eur Radiol; 2024 Sep; 34(9):6132-6144. PubMed ID: 38363315
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Multiparametric MRI-Based Interpretable Radiomics Machine Learning Model Differentiates Medulloblastoma and Ependymoma in Children: A Two-Center Study.
    Yimit Y; Yasin P; Tuersun A; Wang J; Wang X; Huang C; Abudoubari S; Chen X; Ibrahim I; Nijiati P; Wang Y; Zou X; Nijiati M
    Acad Radiol; 2024 Aug; 31(8):3384-3396. PubMed ID: 38508934
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Prediction of breast cancer and axillary positive-node response to neoadjuvant chemotherapy based on multi-parametric magnetic resonance imaging radiomics models.
    Lin Y; Wang J; Li M; Zhou C; Hu Y; Wang M; Zhang X
    Breast; 2024 Aug; 76():103737. PubMed ID: 38696854
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Multi-Parametric Magnetic Resonance Imaging-Based Radiomics Analysis of Cervical Cancer for Preoperative Prediction of Lymphovascular Space Invasion.
    Huang G; Cui Y; Wang P; Ren J; Wang L; Ma Y; Jia Y; Ma X; Zhao L
    Front Oncol; 2021; 11():663370. PubMed ID: 35096556
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI.
    Braman NM; Etesami M; Prasanna P; Dubchuk C; Gilmore H; Tiwari P; Plecha D; Madabhushi A
    Breast Cancer Res; 2017 May; 19(1):57. PubMed ID: 28521821
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Multi-modal radiomics model to predict treatment response to neoadjuvant chemotherapy for locally advanced rectal cancer.
    Li ZY; Wang XD; Li M; Liu XJ; Ye Z; Song B; Yuan F; Yuan Y; Xia CC; Zhang X; Li Q
    World J Gastroenterol; 2020 May; 26(19):2388-2402. PubMed ID: 32476800
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Multiparametric MR Imaging Radiomics Signatures for Assessing the Recurrence Risk of ER+/HER2- Breast Cancer Quantified With 21-Gene Recurrence Score.
    Chen Y; Tang W; Liu W; Li R; Wang Q; Shen X; Gong J; Gu Y; Peng W
    J Magn Reson Imaging; 2023 Aug; 58(2):444-453. PubMed ID: 36440706
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Preoperative prediction of sonic hedgehog and group 4 molecular subtypes of pediatric medulloblastoma based on radiomics of multiparametric MRI combined with clinical parameters.
    Wang Y; Wang L; Qin B; Hu X; Xiao W; Tong Z; Li S; Jing Y; Li L; Zhang Y
    Front Neurosci; 2023; 17():1157858. PubMed ID: 37113160
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Radiomics Based on Multimodal MRI for the Differential Diagnosis of Benign and Malignant Breast Lesions.
    Zhang Q; Peng Y; Liu W; Bai J; Zheng J; Yang X; Zhou L
    J Magn Reson Imaging; 2020 Aug; 52(2):596-607. PubMed ID: 32061014
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Machine learning for prediction of chemoradiation therapy response in rectal cancer using pre-treatment and mid-radiation multi-parametric MRI.
    Shi L; Zhang Y; Nie K; Sun X; Niu T; Yue N; Kwong T; Chang P; Chow D; Chen JH; Su MY
    Magn Reson Imaging; 2019 Sep; 61():33-40. PubMed ID: 31059768
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Application Value of Magnetic Resonance Radiomics and Clinical Nomograms in Evaluating the Sensitivity of Neoadjuvant Chemotherapy for Nasopharyngeal Carcinoma.
    Hu C; Zheng D; Cao X; Pang P; Fang Y; Lu T; Chen Y
    Front Oncol; 2021; 11():740776. PubMed ID: 34790570
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Multiparametric MRI-based machine learning models for preoperatively predicting rectal adenoma with canceration.
    Li P; Song G; Wu R; Li H; Zhang R; Zuo P; Li A
    MAGMA; 2021 Oct; 34(5):707-716. PubMed ID: 33646452
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Radiomics analysis for prediction of lymph node metastasis after neoadjuvant chemotherapy based on pretreatment MRI in patients with locally advanced cervical cancer.
    Liu J; Dong L; Zhang X; Wu Q; Yang Z; Zhang Y; Xu C; Wu Q; Wang M
    Front Oncol; 2024; 14():1376640. PubMed ID: 38779088
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Predicting pathological complete response to neoadjuvant chemotherapy in breast cancer patients: use of MRI radiomics data from three regions with multiple machine learning algorithms.
    Zheng G; Peng J; Shu Z; Jin H; Han L; Yuan Z; Qin X; Hou J; He X; Gong X
    J Cancer Res Clin Oncol; 2024 Mar; 150(3):147. PubMed ID: 38512406
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 37.