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 *

307 related articles for article (PubMed ID: 35035786)

  • 1. Prediction of HER2-positive breast cancer recurrence and metastasis risk from histopathological images and clinical information via multimodal deep learning.
    Yang J; Ju J; Guo L; Ji B; Shi S; Yang Z; Gao S; Yuan X; Tian G; Liang Y; Yuan P
    Comput Struct Biotechnol J; 2022; 20():333-342. PubMed ID: 35035786
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep learning trained on hematoxylin and eosin tumor region of Interest predicts HER2 status and trastuzumab treatment response in HER2+ breast cancer.
    Farahmand S; Fernandez AI; Ahmed FS; Rimm DL; Chuang JH; Reisenbichler E; Zarringhalam K
    Mod Pathol; 2022 Jan; 35(1):44-51. PubMed ID: 34493825
    [TBL] [Abstract][Full Text] [Related]  

  • 3. ICSDA: a multi-modal deep learning model to predict breast cancer recurrence and metastasis risk by integrating pathological, clinical and gene expression data.
    Yao Y; Lv Y; Tong L; Liang Y; Xi S; Ji B; Zhang G; Li L; Tian G; Tang M; Hu X; Li S; Yang J
    Brief Bioinform; 2022 Nov; 23(6):. PubMed ID: 36242564
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Predicting the prognosis of HER2-positive breast cancer patients by fusing pathological whole slide images and clinical features using multiple instance learning.
    Wang Y; Zhang L; Li Y; Wu F; Cao S; Ye F
    Math Biosci Eng; 2023 Apr; 20(6):11196-11211. PubMed ID: 37322978
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Predicting breast cancer recurrence and metastasis risk by integrating color and texture features of histopathological images and machine learning technologies.
    Liu X; Yuan P; Li R; Zhang D; An J; Ju J; Liu C; Ren F; Hou R; Li Y; Yang J
    Comput Biol Med; 2022 Jul; 146():105569. PubMed ID: 35751195
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Prediction of clinicopathological features, multi-omics events and prognosis based on digital pathology and deep learning in HR
    Hu J; Lv H; Zhao S; Lin CJ; Su GH; Shao ZM
    J Thorac Dis; 2023 May; 15(5):2528-2543. PubMed ID: 37324098
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep learning radiopathomics based on preoperative US images and biopsy whole slide images can distinguish between luminal and non-luminal tumors in early-stage breast cancers.
    Huang Y; Yao Z; Li L; Mao R; Huang W; Hu Z; Hu Y; Wang Y; Guo R; Tang X; Yang L; Wang Y; Luo R; Yu J; Zhou J
    EBioMedicine; 2023 Aug; 94():104706. PubMed ID: 37478528
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Lung Cancer Diagnosis on Virtual Histologically Stained Tissue Using Weakly Supervised Learning.
    Chen Z; Wong IHM; Dai W; Lo CTK; Wong TTW
    Mod Pathol; 2024 Jun; 37(6):100487. PubMed ID: 38588884
    [TBL] [Abstract][Full Text] [Related]  

  • 9. DeepLRHE: A Deep Convolutional Neural Network Framework to Evaluate the Risk of Lung Cancer Recurrence and Metastasis From Histopathology Images.
    Wu Z; Wang L; Li C; Cai Y; Liang Y; Mo X; Lu Q; Dong L; Liu Y
    Front Genet; 2020; 11():768. PubMed ID: 33193560
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Deep Learning to Estimate Human Epidermal Growth Factor Receptor 2 Status from Hematoxylin and Eosin-Stained Breast Tissue Images.
    Anand D; Kurian NC; Dhage S; Kumar N; Rane S; Gann PH; Sethi A
    J Pathol Inform; 2020; 11():19. PubMed ID: 33033656
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Deep learning-based predictive model for pathological complete response to neoadjuvant chemotherapy in breast cancer from biopsy pathological images: a multicenter study.
    Zeng H; Qiu S; Zhuang S; Wei X; Wu J; Zhang R; Chen K; Wu Z; Zhuang Z
    Front Physiol; 2024; 15():1279982. PubMed ID: 38357498
    [No Abstract]   [Full Text] [Related]  

  • 12. A Deep Learning Quantification Algorithm for HER2 Scoring of Gastric Cancer.
    Han Z; Lan J; Wang T; Hu Z; Huang Y; Deng Y; Zhang H; Wang J; Chen M; Jiang H; Lee RG; Gao Q; Du M; Tong T; Chen G
    Front Neurosci; 2022; 16():877229. PubMed ID: 35706692
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep learning-based pathological prediction of lymph node metastasis for patient with renal cell carcinoma from primary whole slide images.
    Gao F; Jiang L; Guo T; Lin J; Xu W; Yuan L; Han Y; Yang J; Pan Q; Chen E; Zhang N; Chen S; Wang X
    J Transl Med; 2024 Jun; 22(1):568. PubMed ID: 38877591
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep learning identifies morphological features in breast cancer predictive of cancer ERBB2 status and trastuzumab treatment efficacy.
    Bychkov D; Linder N; Tiulpin A; Kücükel H; Lundin M; Nordling S; Sihto H; Isola J; Lehtimäki T; Kellokumpu-Lehtinen PL; von Smitten K; Joensuu H; Lundin J
    Sci Rep; 2021 Feb; 11(1):4037. PubMed ID: 33597560
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Use of Deep Learning to Develop and Analyze Computational Hematoxylin and Eosin Staining of Prostate Core Biopsy Images for Tumor Diagnosis.
    Rana A; Lowe A; Lithgow M; Horback K; Janovitz T; Da Silva A; Tsai H; Shanmugam V; Bayat A; Shah P
    JAMA Netw Open; 2020 May; 3(5):e205111. PubMed ID: 32432709
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Outcome-Supervised Deep Learning on Pathologic Whole Slide Images for Survival Prediction of Immunotherapy in Patients with Non-Small Cell Lung Cancer.
    Li B; Yang L; Zhang H; Li H; Jiang C; Yao Y; Cheng S; Zou B; Fan B; Dong T; Wang L
    Mod Pathol; 2023 Aug; 36(8):100208. PubMed ID: 37149222
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A multivariable prognostic score to guide systemic therapy in early-stage HER2-positive breast cancer: a retrospective study with an external evaluation.
    Prat A; Guarneri V; Paré L; Griguolo G; Pascual T; Dieci MV; Chic N; González-Farré B; Frassoldati A; Sanfeliu E; Cejalvo JM; Muñoz M; Bisagni G; Brasó-Maristany F; Urso L; Vidal M; Brandes AA; Adamo B; Musolino A; Miglietta F; Conte B; Oliveira M; Saura C; Pernas S; Alarcón J; Llombart-Cussac A; Cortés J; Manso L; López R; Ciruelos E; Schettini F; Villagrasa P; Carey LA; Perou CM; Piacentini F; D'Amico R; Tagliafico E; Parker JS; Conte P
    Lancet Oncol; 2020 Nov; 21(11):1455-1464. PubMed ID: 33152285
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Automated segmentation of cell membranes to evaluate HER2 status in whole slide images using a modified deep learning network.
    Khameneh FD; Razavi S; Kamasak M
    Comput Biol Med; 2019 Jul; 110():164-174. PubMed ID: 31163391
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Deep learning model for the prediction of microsatellite instability in colorectal cancer: a diagnostic study.
    Yamashita R; Long J; Longacre T; Peng L; Berry G; Martin B; Higgins J; Rubin DL; Shen J
    Lancet Oncol; 2021 Jan; 22(1):132-141. PubMed ID: 33387492
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Prediction of Target-Drug Therapy by Identifying Gene Mutations in Lung Cancer With Histopathological Stained Image and Deep Learning Techniques.
    Huang K; Mo Z; Zhu W; Liao B; Yang Y; Wu FX
    Front Oncol; 2021; 11():642945. PubMed ID: 33928031
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.