180 related articles for article (PubMed ID: 37224471)
1. Artificial intelligence-assisted analysis for tumor-immune interaction within the invasive margin of colorectal cancer.
Ye Y; Wu X; Wang H; Ye H; Zhao K; Yao S; Liu Z; Zhu Y; Zhang Q; Liang C
Ann Med; 2023 Dec; 55(1):2215541. PubMed ID: 37224471
[TBL] [Abstract][Full Text] [Related]
2. Artificial intelligence for quantifying immune infiltrates interacting with stroma in colorectal cancer.
Yang J; Ye H; Fan X; Li Y; Wu X; Zhao M; Hu Q; Ye Y; Wu L; Li Z; Zhang X; Liang C; Wang Y; Xu Y; Li Q; Yao S; You D; Zhao K; Liu Z
J Transl Med; 2022 Oct; 20(1):451. PubMed ID: 36195956
[TBL] [Abstract][Full Text] [Related]
3. Development and validation of a scoring system incorporating tumor growth pattern and perineural invasion for risk stratification in colorectal cancer.
Liu Y; Wang Y; Yao S; Liang C; Li Q; Liu Z; Zhu Y; Cui Y; Zhao K
J Investig Med; 2023 Aug; 71(6):674-685. PubMed ID: 37073507
[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. Fully Automated Tumor Bud Assessment in Hematoxylin and Eosin-Stained Whole Slide Images of Colorectal Cancer.
Bokhorst JM; Ciompi F; Öztürk SK; Oguz Erdogan AS; Vieth M; Dawson H; Kirsch R; Simmer F; Sheahan K; Lugli A; Zlobec I; van der Laak J; Nagtegaal ID
Mod Pathol; 2023 Sep; 36(9):100233. PubMed ID: 37257824
[TBL] [Abstract][Full Text] [Related]
6. Artificial intelligence quantified tumour-stroma ratio is an independent predictor for overall survival in resectable colorectal cancer.
Zhao K; Li Z; Yao S; Wang Y; Wu X; Xu Z; Wu L; Huang Y; Liang C; Liu Z
EBioMedicine; 2020 Nov; 61():103054. PubMed ID: 33039706
[TBL] [Abstract][Full Text] [Related]
7. Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study.
Kather JN; Krisam J; Charoentong P; Luedde T; Herpel E; Weis CA; Gaiser T; Marx A; Valous NA; Ferber D; Jansen L; Reyes-Aldasoro CC; Zörnig I; Jäger D; Brenner H; Chang-Claude J; Hoffmeister M; Halama N
PLoS Med; 2019 Jan; 16(1):e1002730. PubMed ID: 30677016
[TBL] [Abstract][Full Text] [Related]
8. Artificial intelligence-based analysis of tumor-infiltrating lymphocyte spatial distribution for colorectal cancer prognosis.
Cai M; Zhao K; Wu L; Huang Y; Zhao M; Hu Q; Chen Q; Yao S; Li Z; Fan X; Liu Z
Chin Med J (Engl); 2024 Feb; 137(4):421-430. PubMed ID: 38238158
[TBL] [Abstract][Full Text] [Related]
9. Clinical impact of heterogeneously distributed tumor-infiltrating lymphocytes on the prognosis of colorectal cancer.
Liu L; Long M; Su S; Wang L; Liu J
PeerJ; 2024; 12():e16747. PubMed ID: 38223758
[TBL] [Abstract][Full Text] [Related]
10. Spatial analysis of tumor-infiltrating lymphocytes in histological sections using deep learning techniques predicts survival in colorectal carcinoma.
Xu H; Cha YJ; Clemenceau JR; Choi J; Lee SH; Kang J; Hwang TH
J Pathol Clin Res; 2022 Jul; 8(4):327-339. PubMed ID: 35484698
[TBL] [Abstract][Full Text] [Related]
11. A deep learning quantified stroma-immune score to predict survival of patients with stage II-III colorectal cancer.
Xu Z; Li Y; Wang Y; Zhang S; Huang Y; Yao S; Han C; Pan X; Shi Z; Mao Y; Xu Y; Huang X; Lin H; Chen X; Liang C; Li Z; Zhao K; Zhang Q; Liu Z
Cancer Cell Int; 2021 Oct; 21(1):585. PubMed ID: 34717647
[TBL] [Abstract][Full Text] [Related]
12. An artificial intelligence-based ecological index for prognostic evaluation of colorectal cancer.
Chen Q; Cai M; Fan X; Liu W; Fang G; Yao S; Xu Y; Li Q; Zhao Y; Zhao K; Liu Z; Chen Z
BMC Cancer; 2023 Aug; 23(1):763. PubMed ID: 37592224
[TBL] [Abstract][Full Text] [Related]
13. CD3+ cells at the invasive margin of deeply invading (pT3-T4) colorectal cancer and risk of post-surgical metastasis: a longitudinal study.
Laghi L; Bianchi P; Miranda E; Balladore E; Pacetti V; Grizzi F; Allavena P; Torri V; Repici A; Santoro A; Mantovani A; Roncalli M; Malesci A
Lancet Oncol; 2009 Sep; 10(9):877-84. PubMed ID: 19656725
[TBL] [Abstract][Full Text] [Related]
14. Artificial intelligence for quantifying Crohn's-like lymphoid reaction and tumor-infiltrating lymphocytes in colorectal cancer.
Xu Y; Yang S; Zhu Y; Yao S; Li Y; Ye H; Ye Y; Li Z; Wu L; Zhao K; Huang L; Liu Z
Comput Struct Biotechnol J; 2022; 20():5586-5594. PubMed ID: 36284712
[TBL] [Abstract][Full Text] [Related]
15. Construction and validation of artificial intelligence pathomics models for predicting pathological staging in colorectal cancer: Using multimodal data and clinical variables.
Tan Y; Liu R; Xue JW; Feng Z
Cancer Med; 2024 Apr; 13(7):e6947. PubMed ID: 38545828
[TBL] [Abstract][Full Text] [Related]
16. A new method for evaluating tumor-infiltrating lymphocytes (TILs) in colorectal cancer using hematoxylin and eosin (H-E)-stained tumor sections.
Iseki Y; Shibutani M; Maeda K; Nagahara H; Fukuoka T; Matsutani S; Kashiwagi S; Tanaka H; Hirakawa K; Ohira M
PLoS One; 2018; 13(4):e0192744. PubMed ID: 29698402
[TBL] [Abstract][Full Text] [Related]
17. Validation of the prognostic value of CD3 and CD8 cell densities analogous to the Immunoscore® by stage and location of colorectal cancer: an independent patient cohort study.
Alwers E; Kather JN; Kloor M; Brobeil A; Tagscherer KE; Roth W; Echle A; Amitay EL; Chang-Claude J; Brenner H; Hoffmeister M
J Pathol Clin Res; 2023 Mar; 9(2):129-136. PubMed ID: 36424650
[TBL] [Abstract][Full Text] [Related]
18. The prognostic value of tumor-infiltrating lymphocytes in colorectal cancer differs by anatomical subsite: a systematic review and meta-analysis.
Zhao Y; Ge X; He J; Cheng Y; Wang Z; Wang J; Sun L
World J Surg Oncol; 2019 May; 17(1):85. PubMed ID: 31118034
[TBL] [Abstract][Full Text] [Related]
19. Automated whole-slide images assessment of immune infiltration in resected non-small-cell lung cancer: towards better risk-stratification.
Lin H; Pan X; Feng Z; Yan L; Hua J; Liang Y; Han C; Xu Z; Wang Y; Wu L; Cui Y; Huang X; Shi Z; Chen X; Chen X; Zhang Q; Liang C; Zhao K; Li Z; Liu Z
J Transl Med; 2022 Jun; 20(1):261. PubMed ID: 35672787
[TBL] [Abstract][Full Text] [Related]
20. Peritumoral tertiary lymphoid structure and tumor stroma percentage predict the prognosis of patients with non-metastatic colorectal cancer.
Wang Q; Shen X; An R; Bai J; Dong J; Cai H; Zhu H; Zhong W; Chen W; Liu A; Du J
Front Immunol; 2022; 13():962056. PubMed ID: 36189233
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
