135 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. 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]
5. 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]
6. 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]
7. 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]
8. 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]
9. Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study.
Muti HS; Heij LR; Keller G; Kohlruss M; Langer R; Dislich B; Cheong JH; Kim YW; Kim H; Kook MC; Cunningham D; Allum WH; Langley RE; Nankivell MG; Quirke P; Hayden JD; West NP; Irvine AJ; Yoshikawa T; Oshima T; Huss R; Grosser B; Roviello F; d'Ignazio A; Quaas A; Alakus H; Tan X; Pearson AT; Luedde T; Ebert MP; Jäger D; Trautwein C; Gaisa NT; Grabsch HI; Kather JN
Lancet Digit Health; 2021 Oct; 3(10):e654-e664. PubMed ID: 34417147
[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. 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]
12. 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]
13. 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]
14. 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]
15. 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]
16. 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]
17. 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]
18. 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]
19. 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]
20. Clinical actionability of triaging DNA mismatch repair deficient colorectal cancer from biopsy samples using deep learning.
Jiang W; Mei WJ; Xu SY; Ling YH; Li WR; Kuang JB; Li HS; Hui H; Li JB; Cai MY; Pan ZZ; Zhang HZ; Li L; Ding PR
EBioMedicine; 2022 Jul; 81():104120. PubMed ID: 35753152
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
