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 *

259 related articles for article (PubMed ID: 36739228)

  • 1. MRI-Based Radiomic Models Outperform Radiologists in Predicting Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.
    Wen L; Liu J; Hu P; Bi F; Liu S; Jian L; Zhu S; Nie S; Cao F; Lu Q; Yu X; Liu K
    Acad Radiol; 2023 Sep; 30 Suppl 1():S176-S184. PubMed ID: 36739228
    [TBL] [Abstract][Full Text] [Related]  

  • 2. MRI Radiomics Model Predicts Pathologic Complete Response of Rectal Cancer Following Chemoradiotherapy.
    Shin J; Seo N; Baek SE; Son NH; Lim JS; Kim NK; Koom WS; Kim S
    Radiology; 2022 May; 303(2):351-358. PubMed ID: 35133200
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Prediction of pathological response and lymph node metastasis after neoadjuvant therapy in rectal cancer through tumor and mesorectal MRI radiomic features.
    Qin S; Liu K; Chen Y; Zhou Y; Zhao W; Yan R; Xin P; Zhu Y; Wang H; Lang N
    Sci Rep; 2024 Sep; 14(1):21927. PubMed ID: 39304726
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Radiomics of locally advanced rectal cancer: machine learning-based prediction of response to neoadjuvant chemoradiotherapy using pre-treatment sagittal T2-weighted MRI.
    Yardimci AH; Kocak B; Sel I; Bulut H; Bektas CT; Cin M; Dursun N; Bektas H; Mermut O; Yardimci VH; Kilickesmez O
    Jpn J Radiol; 2023 Jan; 41(1):71-82. PubMed ID: 35962933
    [TBL] [Abstract][Full Text] [Related]  

  • 5. MRI-based delta-radiomics are predictive of pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer.
    Wan L; Peng W; Zou S; Ye F; Geng Y; Ouyang H; Zhao X; Zhang H
    Acad Radiol; 2021 Nov; 28 Suppl 1():S95-S104. PubMed ID: 33189550
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A multiple-time-scale comparative study for the added value of magnetic resonance imaging-based radiomics in predicting pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer.
    Peng W; Wan L; Wang S; Zou S; Zhao X; Zhang H
    Front Oncol; 2023; 13():1234619. PubMed ID: 37664046
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep learning-based radiomic features for improving neoadjuvant chemoradiation response prediction in locally advanced rectal cancer.
    Fu J; Zhong X; Li N; Van Dams R; Lewis J; Sung K; Raldow AC; Jin J; Qi XS
    Phys Med Biol; 2020 Apr; 65(7):075001. PubMed ID: 32092710
    [TBL] [Abstract][Full Text] [Related]  

  • 8. [Predictive value of combination of MRI tumor regression grade and apparent diffusion coefficient for pathological complete remission after neoadjuvant treatment of locally advanced rectal cancer].
    Xu N; Huang FC; Li WL; Luan X; Jiang YM; He B
    Zhonghua Wei Chang Wai Ke Za Zhi; 2021 Apr; 24(4):359-365. PubMed ID: 33878826
    [No Abstract]   [Full Text] [Related]  

  • 9. Multiparametric MRI-based radiomic model for predicting lymph node metastasis after neoadjuvant chemoradiotherapy in locally advanced rectal cancer.
    Wei Q; Chen L; Hou X; Lin Y; Xie R; Yu X; Zhang H; Wen Z; Wu Y; Liu X; Chen W
    Insights Imaging; 2024 Jun; 15(1):163. PubMed ID: 38922456
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Multiparametric MRI-based Radiomics approaches on predicting response to neoadjuvant chemoradiotherapy (nCRT) in patients with rectal cancer.
    Cheng Y; Luo Y; Hu Y; Zhang Z; Wang X; Yu Q; Liu G; Cui E; Yu T; Jiang X
    Abdom Radiol (NY); 2021 Nov; 46(11):5072-5085. PubMed ID: 34302510
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Treatment response prediction using MRI-based pre-, post-, and delta-radiomic features and machine learning algorithms in colorectal cancer.
    Shayesteh S; Nazari M; Salahshour A; Sandoughdaran S; Hajianfar G; Khateri M; Yaghobi Joybari A; Jozian F; Fatehi Feyzabad SH; Arabi H; Shiri I; Zaidi H
    Med Phys; 2021 Jul; 48(7):3691-3701. PubMed ID: 33894058
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Prediction of locally advanced rectal cancer response to neoadjuvant chemoradiation therapy using volumetric multiparametric MRI-based radiomics.
    El Homsi M; Bane O; Fauveau V; Hectors S; Vietti Violi N; Sylla P; Ko HB; Cuevas J; Carbonell G; Nehlsen A; Vanguri R; Viswanath S; Jambawalikar S; Shaish H; Taouli B
    Abdom Radiol (NY); 2024 Mar; 49(3):791-800. PubMed ID: 38150143
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Radiomics of MRI for pretreatment prediction of pathologic complete response, tumor regression grade, and neoadjuvant rectal score in patients with locally advanced rectal cancer undergoing neoadjuvant chemoradiation: an international multicenter study.
    Shaish H; Aukerman A; Vanguri R; Spinelli A; Armenta P; Jambawalikar S; Makkar J; Bentley-Hibbert S; Del Portillo A; Kiran R; Monti L; Bonifacio C; Kirienko M; Gardner KL; Schwartz L; Keller D
    Eur Radiol; 2020 Nov; 30(11):6263-6273. PubMed ID: 32500192
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Radiomic Features of Primary Rectal Cancers on Baseline T
    Antunes JT; Ofshteyn A; Bera K; Wang EY; Brady JT; Willis JE; Friedman KA; Marderstein EL; Kalady MF; Stein SL; Purysko AS; Paspulati R; Gollamudi J; Madabhushi A; Viswanath SE
    J Magn Reson Imaging; 2020 Nov; 52(5):1531-1541. PubMed ID: 32216127
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Predicting pathological complete response by comparing MRI-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer.
    Li Y; Liu W; Pei Q; Zhao L; Güngör C; Zhu H; Song X; Li C; Zhou Z; Xu Y; Wang D; Tan F; Yang P; Pei H
    Cancer Med; 2019 Dec; 8(17):7244-7252. PubMed ID: 31642204
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Developing a prediction model based on MRI for pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer.
    Wan L; Zhang C; Zhao Q; Meng Y; Zou S; Yang Y; Liu Y; Jiang J; Ye F; Ouyang H; Zhao X; Zhang H
    Abdom Radiol (NY); 2019 Sep; 44(9):2978-2987. PubMed ID: 31327039
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Radiomics signature as a new biomarker for preoperative prediction of neoadjuvant chemoradiotherapy response in locally advanced rectal cancer.
    Zhang Z; Jiang X; Zhang R; Yu T; Liu S; Luo Y
    Diagn Interv Radiol; 2021 May; 27(3):308-314. PubMed ID: 34003118
    [TBL] [Abstract][Full Text] [Related]  

  • 18. [Construction of a model based on multipoint full-layer puncture biopsy for predicting pathological complete response after neoadjuvant therapy for locally advanced rectal cancer].
    Jin Y; Zhai ZW; Sun LT; Xia PD; Hu H; Jiang CQ; Zhao BC; Qu H; Qian Q; Dai Y; Yao HW; Wang ZJ; Han JG
    Zhonghua Wei Chang Wai Ke Za Zhi; 2024 Apr; 27(4):403-411. PubMed ID: 38644246
    [No Abstract]   [Full Text] [Related]  

  • 19. Deep learning radiomics-based prediction of distant metastasis in patients with locally advanced rectal cancer after neoadjuvant chemoradiotherapy: A multicentre study.
    Liu X; Zhang D; Liu Z; Li Z; Xie P; Sun K; Wei W; Dai W; Tang Z; Ding Y; Cai G; Tong T; Meng X; Tian J
    EBioMedicine; 2021 Jul; 69():103442. PubMed ID: 34157487
    [TBL] [Abstract][Full Text] [Related]  

  • 20. MRI T2-weighted sequences-based texture analysis (TA) as a predictor of response to neoadjuvant chemo-radiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC).
    Crimì F; Capelli G; Spolverato G; Bao QR; Florio A; Milite Rossi S; Cecchin D; Albertoni L; Campi C; Pucciarelli S; Stramare R
    Radiol Med; 2020 Dec; 125(12):1216-1224. PubMed ID: 32410063
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.