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 *

236 related articles for article (PubMed ID: 38261897)

  • 1. Comparing three-dimensional and two-dimensional deep-learning, radiomics, and fusion models for predicting occult lymph node metastasis in laryngeal squamous cell carcinoma based on CT imaging: a multicentre, retrospective, diagnostic study.
    Wang W; Liang H; Zhang Z; Xu C; Wei D; Li W; Qian Y; Zhang L; Liu J; Lei D
    EClinicalMedicine; 2024 Jan; 67():102385. PubMed ID: 38261897
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Predicting N2 lymph node metastasis in presurgical stage I-II non-small cell lung cancer using multiview radiomics and deep learning method.
    Zhang H; Liao M; Guo Q; Chen J; Wang S; Liu S; Xiao F
    Med Phys; 2023 Apr; 50(4):2049-2060. PubMed ID: 36563341
    [TBL] [Abstract][Full Text] [Related]  

  • 3. MRI-based deep learning and radiomics for prediction of occult cervical lymph node metastasis and prognosis in early-stage oral and oropharyngeal squamous cell carcinoma: a diagnostic study.
    Lan T; Kuang S; Liang P; Ning C; Li Q; Wang L; Wang Y; Lin Z; Hu H; Yang L; Li J; Liu J; Li Y; Wu F; Chai H; Song X; Huang Y; Duan X; Zeng D; Li J; Cao H
    Int J Surg; 2024 Aug; 110(8):4648-4659. PubMed ID: 38729119
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Prediction of lymph node metastasis in stage T1-2 rectal cancers with MRI-based deep learning.
    Wan L; Hu J; Chen S; Zhao R; Peng W; Liu Y; Hu S; Zou S; Wang S; Zhao X; Zhang H
    Eur Radiol; 2023 May; 33(5):3638-3646. PubMed ID: 36905470
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Predicting occult lymph node metastasis in solid-predominantly invasive lung adenocarcinoma across multiple centers using radiomics-deep learning fusion model.
    Tian W; Yan Q; Huang X; Feng R; Shan F; Geng D; Zhang Z
    Cancer Imaging; 2024 Jan; 24(1):8. PubMed ID: 38216999
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Multimodal data integration using machine learning to predict the risk of clear cell renal cancer metastasis: a retrospective multicentre study.
    Yang Y; Wang J; Ren Q; Yu R; Yuan Z; Jiang Q; Guan S; Tang X; Duan T; Meng X
    Abdom Radiol (NY); 2024 Jul; 49(7):2311-2324. PubMed ID: 38879708
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A deep learning and radiomics fusion model based on contrast-enhanced computer tomography improves preoperative identification of cervical lymph node metastasis of oral squamous cell carcinoma.
    Chen Z; Yu Y; Liu S; Du W; Hu L; Wang C; Li J; Liu J; Zhang W; Peng X
    Clin Oral Investig; 2023 Dec; 28(1):39. PubMed ID: 38151672
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Magnetic resonance imaging-based radiomics and deep learning models for predicting lymph node metastasis of squamous cell carcinoma of the tongue.
    Wang D; He X; Huang C; Li W; Li H; Huang C; Hu C
    Oral Surg Oral Med Oral Pathol Oral Radiol; 2024 Jul; 138(1):214-224. PubMed ID: 38378316
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Dual-energy CT-based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer.
    Li J; Dong D; Fang M; Wang R; Tian J; Li H; Gao J
    Eur Radiol; 2020 Apr; 30(4):2324-2333. PubMed ID: 31953668
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Radiomics analysis of CT imaging improves preoperative prediction of cervical lymph node metastasis in laryngeal squamous cell carcinoma.
    Zhao X; Li W; Zhang J; Tian S; Zhou Y; Xu X; Hu H; Lei D; Wu F
    Eur Radiol; 2023 Feb; 33(2):1121-1131. PubMed ID: 35984515
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Deep-learning-based radiomics of intratumoral and peritumoral MRI images to predict the pathological features of adjuvant radiotherapy in early-stage cervical squamous cell carcinoma.
    Zhang XF; Wu HY; Liang XW; Chen JL; Li J; Zhang S; Liu Z
    BMC Womens Health; 2024 Mar; 24(1):182. PubMed ID: 38504245
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comparison of Traditional Radiomics, Deep Learning Radiomics and Fusion Methods for Axillary Lymph Node Metastasis Prediction in Breast Cancer.
    Li X; Yang L; Jiao X
    Acad Radiol; 2023 Jul; 30(7):1281-1287. PubMed ID: 36376154
    [TBL] [Abstract][Full Text] [Related]  

  • 14. One 3D VOI-based deep learning radiomics strategy, clinical model and radiologists for predicting lymph node metastases in pancreatic ductal adenocarcinoma based on multiphasic contrast-enhanced computer tomography.
    Liao H; Yang J; Li Y; Liang H; Ye J; Liu Y
    Front Oncol; 2022; 12():990156. PubMed ID: 36158647
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Development and validation of CT-based radiomics deep learning signatures to predict lymph node metastasis in non-functional pancreatic neuroendocrine tumors: a multicohort study.
    Gu W; Chen Y; Zhu H; Chen H; Yang Z; Mo S; Zhao H; Chen L; Nakajima T; Yu X; Ji S; Gu Y; Chen J; Tang W
    EClinicalMedicine; 2023 Nov; 65():102269. PubMed ID: 38106556
    [TBL] [Abstract][Full Text] [Related]  

  • 16. The development of a nomogram model for predicting left recurrent laryngeal nerve lymph node metastasis in esophageal cancer based on radiomics and clinical factors.
    Huang YL; Yan C; Lin X; Chen ZP; Lin F; Feng ZP; Ke SK
    Ann Transl Med; 2022 Dec; 10(23):1282. PubMed ID: 36618793
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Efficacy of radiomics model based on the concept of gross tumor volume and clinical target volume in predicting occult lymph node metastasis in non-small cell lung cancer.
    Zeng C; Zhang W; Liu M; Liu J; Zheng Q; Li J; Wang Z; Sun G
    Front Oncol; 2023; 13():1096364. PubMed ID: 37293586
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A comparison of machine learning methods for radiomics modeling in prediction of occult lymph node metastasis in clinical stage IA lung adenocarcinoma patients.
    Liu MW; Zhang X; Wang YM; Jiang X; Jiang JM; Li M; Zhang L
    J Thorac Dis; 2024 Mar; 16(3):1765-1776. PubMed ID: 38617761
    [TBL] [Abstract][Full Text] [Related]  

  • 19. CT radiomics features to predict lymph node metastasis in advanced esophageal squamous cell carcinoma and to discriminate between regional and non-regional lymph node metastasis: a case control study.
    Ou J; Wu L; Li R; Wu CQ; Liu J; Chen TW; Zhang XM; Tang S; Wu YP; Yang LQ; Tan BG; Lu FL
    Quant Imaging Med Surg; 2021 Feb; 11(2):628-640. PubMed ID: 33532263
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Deep learning to predict cervical lymph node metastasis from intraoperative frozen section of tumour in papillary thyroid carcinoma: a multicentre diagnostic study.
    Liu Y; Lai F; Lin B; Gu Y; Chen L; Chen G; Xiao H; Luo S; Pang Y; Xiong D; Li B; Peng S; Lv W; Alexander EK; Xiao H
    EClinicalMedicine; 2023 Jun; 60():102007. PubMed ID: 37251623
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.