BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

40 related articles for article (PubMed ID: 38724768)

  • 1. Machine Learning Model for Predicting Axillary Lymph Node Metastasis in Clinically Node Positive Breast Cancer Based on Peritumoral Ultrasound Radiomics and SHAP Feature Analysis.
    Wang SR; Cao CL; Du TT; Wang JL; Li J; Li WX; Chen M
    J Ultrasound Med; 2024 May; ():. PubMed ID: 38808580
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Development of MRI-Based Deep Learning Signature for Prediction of Axillary Response After NAC in Breast Cancer.
    Zhang B; Yu Y; Mao Y; Wang H; Lv M; Su X; Wang Y; Li Z; Zhang Z; Bian T; Wang Q
    Acad Radiol; 2024 Mar; 31(3):800-811. PubMed ID: 37914627
    [TBL] [Abstract][Full Text] [Related]  

  • 3. An unsupervised learning model based on CT radiomics features accurately predicts axillary lymph node metastasis in breast cancer patients-diagnostic study.
    Qu L; Mei X; Yi Z; Zou Q; Zhou Q; Zhang D; Zhou M; Pei L; Long Q; Meng J; Zhang H; Chen Q; Yi W
    Int J Surg; 2024 Jun; ():. PubMed ID: 38847776
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Delta Radiomics Based on Longitudinal Dual-modal Ultrasound Can Early Predict Response to Neoadjuvant Chemotherapy in Breast Cancer Patients.
    Huang JX; Wu L; Wang XY; Lin SY; Xu YF; Wei MJ; Pei XQ
    Acad Radiol; 2024 May; 31(5):1738-1747. PubMed ID: 38057180
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Advanced Gastric Cancer: CT Radiomics Prediction of Lymph Modes Metastasis After Neoadjuvant Chemotherapy.
    Sun J; Wang Z; Zhu H; Yang Q; Sun Y
    J Imaging Inform Med; 2024 Jun; ():. PubMed ID: 38886288
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Revolutionizing breast cancer Ki-67 diagnosis: ultrasound radiomics and fully connected neural networks (FCNN) combination method.
    Li Y; Long W; Zhou H; Tan T; Xie H
    Breast Cancer Res Treat; 2024 Jun; ():. PubMed ID: 38853220
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Development and Validation of an Ultrasonography-Based Machine Learning Model for Predicting Outcomes of Bruxism Treatments.
    Orhan K; Yazici G; Önder M; Evli C; Volkan-Yazici M; Kolsuz ME; Bağış N; Kafa N; Gönüldaş F
    Diagnostics (Basel); 2024 May; 14(11):. PubMed ID: 38893684
    [TBL] [Abstract][Full Text] [Related]  

  • 8. New Frontiers in Breast Cancer Imaging: The Rise of AI.
    Shamir SB; Sasson AL; Margolies LR; Mendelson DS
    Bioengineering (Basel); 2024 May; 11(5):. PubMed ID: 38790318
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Corrigendum: Deep learning or radiomics based on CT for predicting the response of gastric cancer to neoadjuvant chemotherapy: a meta-analysis and systematic review.
    Bao Z; Du J; Zheng Y; Guo Q; Ji R
    Front Oncol; 2024; 14():1433346. PubMed ID: 38846979
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Management of occult breast cancer with pathological complete response.
    Ren N; Liu S; Shi P; Tian X
    Asian J Surg; 2024 Jun; ():. PubMed ID: 38853115
    [No Abstract]   [Full Text] [Related]  

  • 11. Longitudinal ultrasound-based AI model predicts axillary lymph node response to neoadjuvant chemotherapy in breast cancer: a multicenter study.
    Fu Y; Lei YT; Huang YH; Mei F; Wang S; Yan K; Wang YH; Ma YH; Cui LG
    Eur Radiol; 2024 May; ():. PubMed ID: 38724768
    [TBL] [Abstract][Full Text] [Related]  

  • 12. An ultrasound-based nomogram for predicting axillary node pathologic complete response after neoadjuvant chemotherapy in breast cancer: Modeling and external validation.
    Zheng Q; Yan H; He Y; Wang J; Zhang N; Huo L; Liu Y; Wang L; Xu L; Fan Z
    Cancer; 2024 Apr; 130(S8):1513-1523. PubMed ID: 38427584
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Dynamic contrast-enhanced MRI radiomics nomogram for predicting axillary lymph node metastasis in breast cancer.
    Song D; Yang F; Zhang Y; Guo Y; Qu Y; Zhang X; Zhu Y; Cui S
    Cancer Imaging; 2022 Apr; 22(1):17. PubMed ID: 35379339
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Global challenges and policy solutions in breast cancer control.
    Trapani D; Ginsburg O; Fadelu T; Lin NU; Hassett M; Ilbawi AM; Anderson BO; Curigliano G
    Cancer Treat Rev; 2022 Mar; 104():102339. PubMed ID: 35074727
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Radiomics model based on shear-wave elastography in the assessment of axillary lymph node status in early-stage breast cancer.
    Jiang M; Li CL; Luo XM; Chuan ZR; Chen RX; Tang SC; Lv WZ; Cui XW; Dietrich CF
    Eur Radiol; 2022 Apr; 32(4):2313-2325. PubMed ID: 34671832
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries.
    Sung H; Ferlay J; Siegel RL; Laversanne M; Soerjomataram I; Jemal A; Bray F
    CA Cancer J Clin; 2021 May; 71(3):209-249. PubMed ID: 33538338
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Radiomics Nomogram of DCE-MRI for the Prediction of Axillary Lymph Node Metastasis in Breast Cancer.
    Mao N; Dai Y; Lin F; Ma H; Duan S; Xie H; Zhao W; Hong N
    Front Oncol; 2020; 10():541849. PubMed ID: 33381444
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Development and Validation of a Preoperative Magnetic Resonance Imaging Radiomics-Based Signature to Predict Axillary Lymph Node Metastasis and Disease-Free Survival in Patients With Early-Stage Breast Cancer.
    Yu Y; Tan Y; Xie C; Hu Q; Ouyang J; Chen Y; Gu Y; Li A; Lu N; He Z; Yang Y; Chen K; Ma J; Li C; Ma M; Li X; Zhang R; Zhong H; Ou Q; Zhang Y; He Y; Li G; Wu Z; Su F; Song E; Yao H
    JAMA Netw Open; 2020 Dec; 3(12):e2028086. PubMed ID: 33289845
    [TBL] [Abstract][Full Text] [Related]  

  • 19.
    ; ; . PubMed ID:
    [No Abstract]   [Full Text] [Related]  

  • 20.
    ; ; . PubMed ID:
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 2.