Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

141 related articles for article (PubMed ID: 35177797)

  • 1. Interpretable tumor differentiation grade and microsatellite instability recognition in gastric cancer using deep learning.
    Su F; Li J; Zhao X; Wang B; Hu Y; Sun Y; Ji J
    Lab Invest; 2022 Jun; 102(6):641-649. PubMed ID: 35177797
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Deep learning-based methods for classification of microsatellite instability in endometrial cancer from HE-stained pathological images.
    Zhang Y; Chen S; Wang Y; Li J; Xu K; Chen J; Zhao J
    J Cancer Res Clin Oncol; 2023 Sep; 149(11):8877-8888. PubMed ID: 37150803
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Automated diagnosis of 7 canine skin tumors using machine learning on H&E-stained whole slide images.
    Fragoso-Garcia M; Wilm F; Bertram CA; Merz S; Schmidt A; Donovan T; Fuchs-Baumgartinger A; Bartel A; Marzahl C; Diehl L; Puget C; Maier A; Aubreville M; Breininger K; Klopfleisch R
    Vet Pathol; 2023 Nov; 60(6):865-875. PubMed ID: 37515411
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Utility of artificial intelligence with deep learning of hematoxylin and eosin-stained whole slide images to predict lymph node metastasis in T1 colorectal cancer using endoscopically resected specimens; prediction of lymph node metastasis in T1 colorectal cancer.
    Song JH; Hong Y; Kim ER; Kim SH; Sohn I
    J Gastroenterol; 2022 Sep; 57(9):654-666. PubMed ID: 35802259
    [TBL] [Abstract][Full Text] [Related]  

  • 6. PPsNet: An improved deep learning model for microsatellite instability high prediction in colorectal cancer from whole slide images.
    Lou J; Xu J; Zhang Y; Sun Y; Fang A; Liu J; Mur LAJ; Ji B
    Comput Methods Programs Biomed; 2022 Oct; 225():107095. PubMed ID: 36057226
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A U-Net based framework to quantify glomerulosclerosis in digitized PAS and H&E stained human tissues.
    Gallego J; Swiderska-Chadaj Z; Markiewicz T; Yamashita M; Gabaldon MA; Gertych A
    Comput Med Imaging Graph; 2021 Apr; 89():101865. PubMed ID: 33548823
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Piloting a Deep Learning Model for Predicting Nuclear BAP1 Immunohistochemical Expression of Uveal Melanoma from Hematoxylin-and-Eosin Sections.
    Zhang H; Kalirai H; Acha-Sagredo A; Yang X; Zheng Y; Coupland SE
    Transl Vis Sci Technol; 2020 Sep; 9(2):50. PubMed ID: 32953248
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep learning captures selective features for discrimination of microsatellite instability from pathologic tissue slides of gastric cancer.
    Lee SH; Lee Y; Jang HJ
    Int J Cancer; 2023 Jan; 152(2):298-307. PubMed ID: 36054320
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Frequent microsatellite instability in papillary and solid-type, poorly differentiated adenocarcinomas of the stomach.
    Arai T; Sakurai U; Sawabe M; Honma N; Aida J; Ushio Y; Kanazawa N; Kuroiwa K; Takubo K
    Gastric Cancer; 2013 Oct; 16(4):505-12. PubMed ID: 23274922
    [TBL] [Abstract][Full Text] [Related]  

  • 11. One label is all you need: Interpretable AI-enhanced histopathology for oncology.
    Tavolara TE; Su Z; Gurcan MN; Niazi MKK
    Semin Cancer Biol; 2023 Dec; 97():70-85. PubMed ID: 37832751
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Computational Analysis of Pathological Image Enables Interpretable Prediction for Microsatellite Instability.
    Zhu J; Wu W; Zhang Y; Lin S; Jiang Y; Liu R; Zhang H; Wang X
    Front Oncol; 2022; 12():825353. PubMed ID: 35936712
    [TBL] [Abstract][Full Text] [Related]  

  • 13. DEMoS: a deep learning-based ensemble approach for predicting the molecular subtypes of gastric adenocarcinomas from histopathological images.
    Wang Y; Hu C; Kwok T; Bain CA; Xue X; Gasser RB; Webb GI; Boussioutas A; Shen X; Daly RJ; Song J
    Bioinformatics; 2022 Sep; 38(17):4206-4213. PubMed ID: 35801909
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Fast cross-staining alignment of gigapixel whole slide images with application to prostate cancer and breast cancer analysis.
    Wang CW; Lee YC; Khalil MA; Lin KY; Yu CP; Lien HC
    Sci Rep; 2022 Jul; 12(1):11623. PubMed ID: 35803996
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Multimodal Lung Cancer Subtyping Using Deep Learning Neural Networks on Whole Slide Tissue Images and MALDI MSI.
    Janßen C; Boskamp T; Le'Clerc Arrastia J; Otero Baguer D; Hauberg-Lotte L; Kriegsmann M; Kriegsmann K; Steinbuß G; Casadonte R; Kriegsmann J; Maaß P
    Cancers (Basel); 2022 Dec; 14(24):. PubMed ID: 36551667
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Deep learning based on hematoxylin-eosin staining outperforms immunohistochemistry in predicting molecular subtypes of gastric adenocarcinoma.
    Flinner N; Gretser S; Quaas A; Bankov K; Stoll A; Heckmann LE; Mayer RS; Doering C; Demes MC; Buettner R; Rueschoff J; Wild PJ
    J Pathol; 2022 Jun; 257(2):218-226. PubMed ID: 35119111
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Development and validation of MRI-based deep learning models for prediction of microsatellite instability in rectal cancer.
    Zhang W; Yin H; Huang Z; Zhao J; Zheng H; He D; Li M; Tan W; Tian S; Song B
    Cancer Med; 2021 Jun; 10(12):4164-4173. PubMed ID: 33963688
    [TBL] [Abstract][Full Text] [Related]  

  • 18. MIST: multiple instance learning network based on Swin Transformer for whole slide image classification of colorectal adenomas.
    Cai H; Feng X; Yin R; Zhao Y; Guo L; Fan X; Liao J
    J Pathol; 2023 Feb; 259(2):125-135. PubMed ID: 36318158
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Solid-type poorly differentiated adenocarcinoma of the stomach: clinicopathological and molecular characteristics and histogenesis.
    Arai T; Matsuda Y; Aida J; Takubo K; Ishiwata T
    Gastric Cancer; 2019 Mar; 22(2):314-322. PubMed ID: 30088163
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 8.