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 *

367 related articles for article (PubMed ID: 33119899)

  • 1. Deep learning-based radiomics predicts response to chemotherapy in colorectal liver metastases.
    Wei J; Cheng J; Gu D; Chai F; Hong N; Wang Y; Tian J
    Med Phys; 2021 Jan; 48(1):513-522. PubMed ID: 33119899
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Radiomics Texture Analysis for the Identification of Colorectal Liver Metastases Sensitive to First-Line Oxaliplatin-Based Chemotherapy.
    Nakanishi R; Oki E; Hasuda H; Sano E; Miyashita Y; Sakai A; Koga N; Kuriyama N; Nonaka K; Fujimoto Y; Jogo T; Hokonohara K; Hu Q; Hisamatsu Y; Ando K; Kimura Y; Yoshizumi T; Mori M
    Ann Surg Oncol; 2021 Jun; 28(6):2975-2985. PubMed ID: 33454878
    [TBL] [Abstract][Full Text] [Related]  

  • 3. CT-based radiomics for the identification of colorectal cancer liver metastases sensitive to first-line irinotecan-based chemotherapy.
    Qi W; Yang J; Zheng L; Lu Y; Liu R; Ju Y; Niu T; Wang D
    Med Phys; 2023 May; 50(5):2705-2714. PubMed ID: 36841949
    [TBL] [Abstract][Full Text] [Related]  

  • 4. MRI-Based Radiomics Nomogram for Preoperatively Differentiating Intrahepatic Mass-Forming Cholangiocarcinoma From Resectable Colorectal Liver Metastases.
    Xu Y; Ye F; Li L; Yang Y; Ouyang J; Zhou Y; Wang S; Xie L; Zhou J; Zhao H; Zhao X
    Acad Radiol; 2023 Sep; 30(9):2010-2020. PubMed ID: 37414635
    [TBL] [Abstract][Full Text] [Related]  

  • 5. CT radiomics models are unable to predict new liver metastasis after successful thermal ablation of colorectal liver metastases.
    Taghavi M; Staal FC; Simões R; Hong EK; Lambregts DM; van der Heide UA; Beets-Tan RG; Maas M
    Acta Radiol; 2023 Jan; 64(1):5-12. PubMed ID: 34918955
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A CT-based radiomics nomogram for predicting histopathologic growth patterns of colorectal liver metastases.
    Sun C; Liu X; Sun J; Dong L; Wei F; Bao C; Zhong J; Li Y
    J Cancer Res Clin Oncol; 2023 Sep; 149(12):9543-9555. PubMed ID: 37221440
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Independent validation of CT radiomics models in colorectal liver metastases: predicting local tumour progression after ablation.
    van der Reijd DJ; Guerendel C; Staal FCR; Busard MP; De Oliveira Taveira M; Klompenhouwer EG; Kuhlmann KFD; Moelker A; Verhoef C; Starmans MPA; Lambregts DMJ; Beets-Tan RGH; Benson S; Maas M
    Eur Radiol; 2024 Jun; 34(6):3635-3643. PubMed ID: 37987835
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A predictive model for early therapeutic efficacy of colorectal liver metastases using multimodal MRI data.
    Su X; Zhang H; Wang Y
    J Xray Sci Technol; 2023; 31(2):357-372. PubMed ID: 36591694
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Development and validation of a deep learning signature for predicting lymph node metastasis in lung adenocarcinoma: comparison with radiomics signature and clinical-semantic model.
    Ma X; Xia L; Chen J; Wan W; Zhou W
    Eur Radiol; 2023 Mar; 33(3):1949-1962. PubMed ID: 36169691
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Deep learning-assisted magnetic resonance imaging prediction of tumor response to chemotherapy in patients with colorectal liver metastases.
    Zhu HB; Xu D; Ye M; Sun L; Zhang XY; Li XT; Nie P; Xing BC; Sun YS
    Int J Cancer; 2021 Apr; 148(7):1717-1730. PubMed ID: 33284998
    [TBL] [Abstract][Full Text] [Related]  

  • 11. CT-Based Radiomics Analysis Before Thermal Ablation to Predict Local Tumor Progression for Colorectal Liver Metastases.
    Taghavi M; Staal F; Gomez Munoz F; Imani F; Meek DB; Simões R; Klompenhouwer LG; van der Heide UA; Beets-Tan RGH; Maas M
    Cardiovasc Intervent Radiol; 2021 Jun; 44(6):913-920. PubMed ID: 33506278
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Magnetic resonance imaging-radiomics evaluation of response to chemotherapy for synchronous liver metastasis of colorectal cancer.
    Ma YQ; Wen Y; Liang H; Zhong JG; Pang PP
    World J Gastroenterol; 2021 Oct; 27(38):6465-6475. PubMed ID: 34720535
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep learning radiomics based on contrast enhanced computed tomography predicts microvascular invasion and survival outcome in early stage hepatocellular carcinoma.
    Yang Y; Zhou Y; Zhou C; Ma X
    Eur J Surg Oncol; 2022 May; 48(5):1068-1077. PubMed ID: 34862094
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A clinical-radiomics model incorporating T2-weighted and diffusion-weighted magnetic resonance images predicts the existence of lymphovascular invasion / perineural invasion in patients with colorectal cancer.
    Zhang K; Ren Y; Xu S; Lu W; Xie S; Qu J; Wang X; Shen B; Pang P; Cai X; Sun J
    Med Phys; 2021 Sep; 48(9):4872-4882. PubMed ID: 34042185
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Dual-Energy CT Deep Learning Radiomics to Predict Macrotrabecular-Massive Hepatocellular Carcinoma.
    Li M; Fan Y; You H; Li C; Luo M; Zhou J; Li A; Zhang L; Yu X; Deng W; Zhou J; Zhang D; Zhang Z; Chen H; Xiao Y; Huang B; Wang J
    Radiology; 2023 Aug; 308(2):e230255. PubMed ID: 37606573
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Predicting response to neoadjuvant chemotherapy for colorectal liver metastasis using deep learning on prechemotherapy cross-sectional imaging.
    Davis JMK; Niazi MKK; Ricker AB; Tavolara TE; Robinson JN; Annanurov B; Smith K; Mantha R; Hwang J; Shrestha R; Iannitti DA; Martinie JB; Baker EH; Gurcan MN; Vrochides D
    J Surg Oncol; 2024 Jul; 130(1):93-101. PubMed ID: 38712939
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Development and validation of a deep learning radiomics model with clinical-radiological characteristics for the identification of occult peritoneal metastases in patients with pancreatic ductal adenocarcinoma.
    Shi S; Lin C; Zhou J; Wei L; Chen M; Zhang J; Cao K; Fan Y; Huang B; Luo Y; Feng ST
    Int J Surg; 2024 May; 110(5):2669-2678. PubMed ID: 38445459
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep learning model based on contrast-enhanced ultrasound for predicting early recurrence after thermal ablation of colorectal cancer liver metastasis.
    Zhao QX; He XL; Wang K; Cheng ZG; Han ZY; Liu FY; Yu XL; Hui Z; Yu J; Chao A; Liang P
    Eur Radiol; 2023 Mar; 33(3):1895-1905. PubMed ID: 36418624
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Advanced image analytics predicting clinical outcomes in patients with colorectal liver metastases: A systematic review of the literature.
    Wesdorp NJ; van Goor VJ; Kemna R; Jansma EP; van Waesberghe JHTM; Swijnenburg RJ; Punt CJA; Huiskens J; Kazemier G
    Surg Oncol; 2021 Sep; 38():101578. PubMed ID: 33866191
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Deep Learning Radiomics Nomogram Based on Enhanced CT to Predict the Response of Metastatic Lymph Nodes to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer.
    Zhong H; Wang T; Hou M; Liu X; Tian Y; Cao S; Li Z; Han Z; Liu G; Sun Y; Meng C; Li Y; Jiang Y; Ji Q; Hao D; Liu Z; Zhou Y
    Ann Surg Oncol; 2024 Jan; 31(1):421-432. PubMed ID: 37925653
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 19.