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.
162 related articles for article (PubMed ID: 34708036)
21. Exploration of predictive and prognostic alternative splicing signatures in lung adenocarcinoma using machine learning methods. Cai Q; He B; Zhang P; Zhao Z; Peng X; Zhang Y; Xie H; Wang X J Transl Med; 2020 Dec; 18(1):463. PubMed ID: 33287830 [TBL] [Abstract][Full Text] [Related]
22. Integrating genetic mutations and expression profiles for survival prediction of lung adenocarcinoma. Song Y; Chen D; Zhang X; Luo Y; Li S Thorac Cancer; 2019 May; 10(5):1220-1228. PubMed ID: 30993904 [TBL] [Abstract][Full Text] [Related]
23. Establishment of a pathomic-based machine learning model to predict CD276 (B7-H3) expression in colon cancer. Li J; Wang D; Zhang C Front Oncol; 2023; 13():1232192. PubMed ID: 38260829 [TBL] [Abstract][Full Text] [Related]
24. Development of a novel prognostic score combining clinicopathologic variables, gene expression, and mutation profiles for lung adenocarcinoma. Li G; Wang G; Guo Y; Li S; Zhang Y; Li J; Peng B World J Surg Oncol; 2020 Sep; 18(1):249. PubMed ID: 32950055 [TBL] [Abstract][Full Text] [Related]
25. Clinical use of a machine learning histopathological image signature in diagnosis and survival prediction of clear cell renal cell carcinoma. Chen S; Zhang N; Jiang L; Gao F; Shao J; Wang T; Zhang E; Yu H; Wang X; Zheng J Int J Cancer; 2021 Feb; 148(3):780-790. PubMed ID: 32895914 [TBL] [Abstract][Full Text] [Related]
26. Multi-Organ Omics-Based Prediction for Adaptive Radiation Therapy Eligibility in Nasopharyngeal Carcinoma Patients Undergoing Concurrent Chemoradiotherapy. Lam SK; Zhang Y; Zhang J; Li B; Sun JC; Liu CY; Chou PH; Teng X; Ma ZR; Ni RY; Zhou T; Peng T; Xiao HN; Li T; Ren G; Cheung AL; Lee FK; Yip CW; Au KH; Lee VH; Chang AT; Chan LW; Cai J Front Oncol; 2021; 11():792024. PubMed ID: 35174068 [TBL] [Abstract][Full Text] [Related]
27. Identification of a four-gene panel predicting overall survival for lung adenocarcinoma. Li C; Long Q; Zhang D; Li J; Zhang X BMC Cancer; 2020 Dec; 20(1):1198. PubMed ID: 33287749 [TBL] [Abstract][Full Text] [Related]
28. Identification of a 6-gene signature for the survival prediction of breast cancer patients based on integrated multi-omics data analysis. Mo W; Ding Y; Zhao S; Zou D; Ding X PLoS One; 2020; 15(11):e0241924. PubMed ID: 33170908 [TBL] [Abstract][Full Text] [Related]
29. Building trans-omics evidence: using imaging and 'omics' to characterize cancer profiles. Srivastava A; Kulkarni C; Mallick P; Huang K; Machiraju R Pac Symp Biocomput; 2018; 23():377-387. PubMed ID: 29218898 [TBL] [Abstract][Full Text] [Related]
31. Allele frequency deviation (AFD) as a new prognostic model to predict overall survival in lung adenocarcinoma (LUAD). Al-Dherasi A; Liao Y; Al-Mosaib S; Hua R; Wang Y; Yu Y; Zhang Y; Zhang X; Jalayta R; Mousa H; Al-Danakh A; Alnadari F; Almoiliqy M; Baldi S; Shi L; Lv D; Li Z; Liu Q Cancer Cell Int; 2021 Aug; 21(1):451. PubMed ID: 34446004 [TBL] [Abstract][Full Text] [Related]
32. Radiomics MRI Phenotyping with Machine Learning to Predict the Grade of Lower-Grade Gliomas: A Study Focused on Nonenhancing Tumors. Park YW; Choi YS; Ahn SS; Chang JH; Kim SH; Lee SK Korean J Radiol; 2019 Sep; 20(9):1381-1389. PubMed ID: 31464116 [TBL] [Abstract][Full Text] [Related]
33. Development and validation of a 4-gene combination for the prognostication in lung adenocarcinoma patients. Yin XH; Yu LP; Zhao XH; Li QM; Liu XP; He L J Cancer; 2020; 11(7):1940-1948. PubMed ID: 32194805 [No Abstract] [Full Text] [Related]
34. An eight-miRNA signature as a potential biomarker for predicting survival in lung adenocarcinoma. Li X; Shi Y; Yin Z; Xue X; Zhou B J Transl Med; 2014 Jun; 12():159. PubMed ID: 24893932 [TBL] [Abstract][Full Text] [Related]
35. Construction and validation of a novel prognostic signature of microRNAs in lung adenocarcinoma. Li W; Liu S; Su S; Chen Y; Sun G PeerJ; 2021; 9():e10470. PubMed ID: 33510968 [TBL] [Abstract][Full Text] [Related]
36. Predicting censored survival data based on the interactions between meta-dimensional omics data in breast cancer. Kim D; Li R; Dudek SM; Ritchie MD J Biomed Inform; 2015 Aug; 56():220-8. PubMed ID: 26048077 [TBL] [Abstract][Full Text] [Related]
37. Deep learning assisted multi-omics integration for survival and drug-response prediction in breast cancer. Malik V; Kalakoti Y; Sundar D BMC Genomics; 2021 Mar; 22(1):214. PubMed ID: 33761889 [TBL] [Abstract][Full Text] [Related]
38. A Translational Pipeline for Overall Survival Prediction of Breast Cancer Patients by Decision-Level Integration of Multi-Omics Data. Mitchel J; Chatlin K; Tong L; Wang MD Proceedings (IEEE Int Conf Bioinformatics Biomed); 2019 Nov; 2019():1573-1580. PubMed ID: 32601549 [TBL] [Abstract][Full Text] [Related]
39. Prediction of pathologic stage in non-small cell lung cancer using machine learning algorithm based on CT image feature analysis. Yu L; Tao G; Zhu L; Wang G; Li Z; Ye J; Chen Q BMC Cancer; 2019 May; 19(1):464. PubMed ID: 31101024 [TBL] [Abstract][Full Text] [Related]
40. Development of an Oncogenic Driver Alteration Associated Immune-Related Prognostic Model for Stage I-II Lung Adenocarcinoma. Xu JZ; Gong C; Xie ZF; Zhao H Front Oncol; 2020; 10():593022. PubMed ID: 33585210 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]