562 related articles for article (PubMed ID: 34686474)
21. A Novel and Efficient Digital Pathology Classifier for Predicting Cancer Biomarkers Using Sequencer Architecture.
Cen M; Li X; Guo B; Jonnagaddala J; Zhang H; Xu XS
Am J Pathol; 2023 Dec; 193(12):2122-2132. PubMed ID: 37775043
[TBL] [Abstract][Full Text] [Related]
22. 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]
23. Association between molecular subtypes of colorectal cancer and patient survival.
Phipps AI; Limburg PJ; Baron JA; Burnett-Hartman AN; Weisenberger DJ; Laird PW; Sinicrope FA; Rosty C; Buchanan DD; Potter JD; Newcomb PA
Gastroenterology; 2015 Jan; 148(1):77-87.e2. PubMed ID: 25280443
[TBL] [Abstract][Full Text] [Related]
24. Deep learning image analysis quantifies tumor heterogeneity and identifies microsatellite instability in colon cancer.
Rubinstein JC; Foroughi Pour A; Zhou J; Sheridan TB; White BS; Chuang JH
J Surg Oncol; 2023 Mar; 127(3):426-433. PubMed ID: 36251352
[TBL] [Abstract][Full Text] [Related]
25. Mutations in both KRAS and BRAF may contribute to the methylator phenotype in colon cancer.
Nagasaka T; Koi M; Kloor M; Gebert J; Vilkin A; Nishida N; Shin SK; Sasamoto H; Tanaka N; Matsubara N; Boland CR; Goel A
Gastroenterology; 2008 Jun; 134(7):1950-60, 1960.e1. PubMed ID: 18435933
[TBL] [Abstract][Full Text] [Related]
26. Feasibility of deep learning-based fully automated classification of microsatellite instability in tissue slides of colorectal cancer.
Lee SH; Song IH; Jang HJ
Int J Cancer; 2021 Aug; 149(3):728-740. PubMed ID: 33851412
[TBL] [Abstract][Full Text] [Related]
27. TGFBR2 mutation is correlated with CpG island methylator phenotype in microsatellite instability-high colorectal cancer.
Ogino S; Kawasaki T; Ogawa A; Kirkner GJ; Loda M; Fuchs CS
Hum Pathol; 2007 Apr; 38(4):614-20. PubMed ID: 17270239
[TBL] [Abstract][Full Text] [Related]
28. Evaluation and identification of factors related to
Lin L; Chen GY; Xu CW; Wang HY; Wu YF; Fang MY
J Cancer Res Ther; 2016 Dec; 12(Supplement):C191-C198. PubMed ID: 28230016
[TBL] [Abstract][Full Text] [Related]
29. Predicting colorectal cancer microsatellite instability with a self-attention-enabled convolutional neural network.
Chang X; Wang J; Zhang G; Yang M; Xi Y; Xi C; Chen G; Nie X; Meng B; Quan X
Cell Rep Med; 2023 Feb; 4(2):100914. PubMed ID: 36720223
[TBL] [Abstract][Full Text] [Related]
30. PIK3CA and PTEN gene and exon mutation-specific clinicopathologic and molecular associations in colorectal cancer.
Day FL; Jorissen RN; Lipton L; Mouradov D; Sakthianandeswaren A; Christie M; Li S; Tsui C; Tie J; Desai J; Xu ZZ; Molloy P; Whitehall V; Leggett BA; Jones IT; McLaughlin S; Ward RL; Hawkins NJ; Ruszkiewicz AR; Moore J; Busam D; Zhao Q; Strausberg RL; Gibbs P; Sieber OM
Clin Cancer Res; 2013 Jun; 19(12):3285-96. PubMed ID: 23633456
[TBL] [Abstract][Full Text] [Related]
31. Deep neural network for the prediction of KRAS, NRAS, and BRAF genotypes in left-sided colorectal cancer based on histopathologic images.
Li X; Chi X; Huang P; Liang Q; Liu J
Comput Med Imaging Graph; 2024 Jul; 115():102384. PubMed ID: 38759471
[TBL] [Abstract][Full Text] [Related]
32. Tumour mutational burden, microsatellite instability, and actionable alterations in metastatic colorectal cancer: Next-generation sequencing results of TRIBE2 study.
Antoniotti C; Korn WM; Marmorino F; Rossini D; Lonardi S; Masi G; Randon G; Conca V; Boccaccino A; Tomasello G; Passardi A; Swensen J; Ugolini C; Oberley M; Tamburini E; Casagrande M; Domenyuk V; Fontanini G; Giordano M; Abraham J; Spetzler D; Falcone A; Lenz HJ; Cremolini C
Eur J Cancer; 2021 Sep; 155():73-84. PubMed ID: 34365081
[TBL] [Abstract][Full Text] [Related]
33. Association Between Molecular Subtypes of Colorectal Tumors and Patient Survival, Based on Pooled Analysis of 7 International Studies.
Phipps AI; Alwers E; Harrison T; Banbury B; Brenner H; Campbell PT; Chang-Claude J; Buchanan D; Chan AT; Farris AB; Figueiredo JC; Gallinger S; Giles GG; Jenkins M; Milne RL; Newcomb PA; Slattery ML; Song M; Ogino S; Zaidi SH; Hoffmeister M; Peters U
Gastroenterology; 2020 Jun; 158(8):2158-2168.e4. PubMed ID: 32088204
[TBL] [Abstract][Full Text] [Related]
34. Unique characteristics of CpG island methylator phenotype (CIMP) in a Chinese population with colorectal cancer.
Liu J; Tang L; Yi J; Li G; Lu Y; Xu Y; Zhao S; Mao R; Li X; Ren L; Wang K
BMC Gastroenterol; 2019 Nov; 19(1):173. PubMed ID: 31690257
[TBL] [Abstract][Full Text] [Related]
35. The impact of CpG island methylator phenotype and microsatellite instability on tumour budding in colorectal cancer.
Zlobec I; Bihl MP; Foerster A; Rufle A; Lugli A
Histopathology; 2012 Nov; 61(5):777-87. PubMed ID: 22803799
[TBL] [Abstract][Full Text] [Related]
36. Assessment of colorectal cancer molecular features along bowel subsites challenges the conception of distinct dichotomy of proximal versus distal colorectum.
Yamauchi M; Morikawa T; Kuchiba A; Imamura Y; Qian ZR; Nishihara R; Liao X; Waldron L; Hoshida Y; Huttenhower C; Chan AT; Giovannucci E; Fuchs C; Ogino S
Gut; 2012 Jun; 61(6):847-54. PubMed ID: 22427238
[TBL] [Abstract][Full Text] [Related]
37. Smoking, alcohol consumption and colorectal cancer risk by molecular pathological subtypes and pathways.
Amitay EL; Carr PR; Jansen L; Roth W; Alwers E; Herpel E; Kloor M; Bläker H; Chang-Claude J; Brenner H; Hoffmeister M
Br J Cancer; 2020 May; 122(11):1604-1610. PubMed ID: 32225169
[TBL] [Abstract][Full Text] [Related]
38. Methylator phenotype in colorectal cancer: A prognostic factor or not?
Gallois C; Laurent-Puig P; Taieb J
Crit Rev Oncol Hematol; 2016 Mar; 99():74-80. PubMed ID: 26702883
[TBL] [Abstract][Full Text] [Related]
39. Prediction of clinically actionable genetic alterations from colorectal cancer histopathology images using deep learning.
Jang HJ; Lee A; Kang J; Song IH; Lee SH
World J Gastroenterol; 2020 Oct; 26(40):6207-6223. PubMed ID: 33177794
[TBL] [Abstract][Full Text] [Related]
40. Attention-based multiple instance learning with self-supervision to predict microsatellite instability in colorectal cancer from histology whole-slide images.
Leiby JS; Hao J; Kang GH; Park JW; Kim D
Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():3068-3071. PubMed ID: 36085965
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
