BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

786 related articles for article (PubMed ID: 30328048)

  • 1. Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set.
    Cain EH; Saha A; Harowicz MR; Marks JR; Marcom PK; Mazurowski MA
    Breast Cancer Res Treat; 2019 Jan; 173(2):455-463. PubMed ID: 30328048
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Machine learning on MRI radiomic features: identification of molecular subtype alteration in breast cancer after neoadjuvant therapy.
    Liu HQ; Lin SY; Song YD; Mai SY; Yang YD; Chen K; Wu Z; Zhao HY
    Eur Radiol; 2023 Apr; 33(4):2965-2974. PubMed ID: 36418622
    [TBL] [Abstract][Full Text] [Related]  

  • 4. MRI-based machine learning radiomics can predict HER2 expression level and pathologic response after neoadjuvant therapy in HER2 overexpressing breast cancer.
    Bitencourt AGV; Gibbs P; Rossi Saccarelli C; Daimiel I; Lo Gullo R; Fox MJ; Thakur S; Pinker K; Morris EA; Morrow M; Jochelson MS
    EBioMedicine; 2020 Nov; 61():103042. PubMed ID: 33039708
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. Four-Dimensional Machine Learning Radiomics for the Pretreatment Assessment of Breast Cancer Pathologic Complete Response to Neoadjuvant Chemotherapy in Dynamic Contrast-Enhanced MRI.
    Caballo M; Sanderink WBG; Han L; Gao Y; Athanasiou A; Mann RM
    J Magn Reson Imaging; 2023 Jan; 57(1):97-110. PubMed ID: 35633290
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Role of
    Akimoto E; Kadoya T; Kajitani K; Emi A; Shigematsu H; Ohara M; Masumoto N; Okada M
    Clin Breast Cancer; 2018 Feb; 18(1):45-52. PubMed ID: 28993056
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Machine learning for diagnostic ultrasound of triple-negative breast cancer.
    Wu T; Sultan LR; Tian J; Cary TW; Sehgal CM
    Breast Cancer Res Treat; 2019 Jan; 173(2):365-373. PubMed ID: 30343454
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A machine learning model that classifies breast cancer pathologic complete response on MRI post-neoadjuvant chemotherapy.
    Sutton EJ; Onishi N; Fehr DA; Dashevsky BZ; Sadinski M; Pinker K; Martinez DF; Brogi E; Braunstein L; Razavi P; El-Tamer M; Sacchini V; Deasy JO; Morris EA; Veeraraghavan H
    Breast Cancer Res; 2020 May; 22(1):57. PubMed ID: 32466777
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Novel computational biology modeling system can accurately forecast response to neoadjuvant therapy in early breast cancer.
    Peterson JR; Cole JA; Pfeiffer JR; Norris GH; Zhang Y; Lopez-Ramos D; Pandey T; Biancalana M; Esslinger HR; Antony AK; Takiar V
    Breast Cancer Res; 2023 May; 25(1):54. PubMed ID: 37165441
    [TBL] [Abstract][Full Text] [Related]  

  • 12. MRI-based tumor shrinkage patterns after early neoadjuvant therapy in breast cancer: correlation with molecular subtypes and pathological response after therapy.
    Wang M; Du S; Gao S; Zhao R; Liu S; Jiang W; Peng C; Chai R; Zhang L
    Breast Cancer Res; 2024 Feb; 26(1):26. PubMed ID: 38347619
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Development and validation of a nomogram based on pretreatment dynamic contrast-enhanced MRI for the prediction of pathologic response after neoadjuvant chemotherapy for triple-negative breast cancer.
    Li Y; Chen Y; Zhao R; Ji Y; Li J; Zhang Y; Lu H
    Eur Radiol; 2022 Mar; 32(3):1676-1687. PubMed ID: 34767068
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Predicting the response to neoadjuvant chemotherapy for breast cancer: wavelet transforming radiomics in MRI.
    Zhou J; Lu J; Gao C; Zeng J; Zhou C; Lai X; Cai W; Xu M
    BMC Cancer; 2020 Feb; 20(1):100. PubMed ID: 32024483
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Imaging and Clinicopathologic Features Associated With Pathologic Complete Response in HER2-positive Breast Cancer Receiving Neoadjuvant Chemotherapy With Dual HER2 Blockade.
    Yoon GY; Chae EY; Cha JH; Shin HJ; Choi WJ; Kim HH; Kim JE; Kim SB
    Clin Breast Cancer; 2020 Feb; 20(1):25-32. PubMed ID: 31519449
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Evaluation of the Tumor Response After Neoadjuvant Chemotherapy in Breast Cancer Patients: Correlation Between Dynamic Contrast-enhanced Magnetic Resonance Imaging and Pathologic Tumor Cellularity.
    Choi WJ; Kim WK; Shin HJ; Cha JH; Chae EY; Kim HH
    Clin Breast Cancer; 2018 Feb; 18(1):e115-e121. PubMed ID: 28890184
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Dynamic Contrast-Enhanced MRI Evaluation of Pathologic Complete Response in Human Epidermal Growth Factor Receptor 2 (HER2)-Positive Breast Cancer After HER2-Targeted Therapy.
    Heacock L; Lewin A; Ayoola A; Moccaldi M; Babb JS; Kim SG; Moy L
    Acad Radiol; 2020 May; 27(5):e87-e93. PubMed ID: 31444111
    [TBL] [Abstract][Full Text] [Related]  

  • 18. MRI staging after neoadjuvant chemotherapy for breast cancer: does tumor biology affect accuracy?
    McGuire KP; Toro-Burguete J; Dang H; Young J; Soran A; Zuley M; Bhargava R; Bonaventura M; Johnson R; Ahrendt G
    Ann Surg Oncol; 2011 Oct; 18(11):3149-54. PubMed ID: 21947592
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Radiomics features based on automatic segmented MRI images: Prognostic biomarkers for triple-negative breast cancer treated with neoadjuvant chemotherapy.
    Ma M; Gan L; Liu Y; Jiang Y; Xin L; Liu Y; Qin N; Cheng Y; Liu Q; Xu L; Zhang Y; Wang X; Zhang X; Ye J; Wang X
    Eur J Radiol; 2022 Jan; 146():110095. PubMed ID: 34890936
    [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 40.