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.
126 related articles for article (PubMed ID: 28393144)
1. Exploration of Genomic, Proteomic, and Histopathological Image Data Integration Methods for Clinical Prediction. Poruthoor A; Phan JH; Kothari S; Wang MD IEEE China Summit Int Conf Signal Inf Process; 2013 Jul; 2013():259-263. PubMed ID: 28393144 [TBL] [Abstract][Full Text] [Related]
2. Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival. Phan JH; Hoffman R; Kothari S; Wu PY; Wang MD IEEE EMBS Int Conf Biomed Health Inform; 2016 Feb; 2016():577-580. PubMed ID: 27493999 [TBL] [Abstract][Full Text] [Related]
3. A multi-modal fusion framework based on multi-task correlation learning for cancer prognosis prediction. Tan K; Huang W; Liu X; Hu J; Dong S Artif Intell Med; 2022 Apr; 126():102260. PubMed ID: 35346442 [TBL] [Abstract][Full Text] [Related]
4. TransSurv: Transformer-Based Survival Analysis Model Integrating Histopathological Images and Genomic Data for Colorectal Cancer. Lv Z; Lin Y; Yan R; Wang Y; Zhang F IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(6):3411-3420. PubMed ID: 35976825 [TBL] [Abstract][Full Text] [Related]
5. Integration of histopathological images and multi-dimensional omics analyses predicts molecular features and prognosis in high-grade serous ovarian cancer. Zeng H; Chen L; Zhang M; Luo Y; Ma X Gynecol Oncol; 2021 Oct; 163(1):171-180. PubMed ID: 34275655 [TBL] [Abstract][Full Text] [Related]
6. Incorporating inter-relationships between different levels of genomic data into cancer clinical outcome prediction. Kim D; Shin H; Sohn KA; Verma A; Ritchie MD; Kim JH Methods; 2014 Jun; 67(3):344-53. PubMed ID: 24561168 [TBL] [Abstract][Full Text] [Related]
7. Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction. Kim D; Joung JG; Sohn KA; Shin H; Park YR; Ritchie MD; Kim JH J Am Med Inform Assoc; 2015 Jan; 22(1):109-20. PubMed ID: 25002459 [TBL] [Abstract][Full Text] [Related]
8. The Cancer Genome Atlas Clinical Explorer: a web and mobile interface for identifying clinical-genomic driver associations. Lee H; Palm J; Grimes SM; Ji HP Genome Med; 2015 Oct; 7():112. PubMed ID: 26507825 [TBL] [Abstract][Full Text] [Related]
9. Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer. Tong L; Wu H; Wang MD Methods; 2021 May; 189():74-85. PubMed ID: 32763377 [TBL] [Abstract][Full Text] [Related]
10. Multi-modal Learning with Missing Data for Cancer Diagnosis Using Histopathological and Genomic Data. Cui C; Asad Z; Dean WF; Smith IT; Madden C; Bao S; Landman BA; Roland JT; Coburn LA; Wilson KT; Zwerner JP; Zhao S; Wheless LE; Huo Y Proc SPIE Int Soc Opt Eng; 2022; 12033():. PubMed ID: 36304178 [TBL] [Abstract][Full Text] [Related]
11. Deep learning based feature-level integration of multi-omics data for breast cancer patients survival analysis. Tong L; Mitchel J; Chatlin K; Wang MD BMC Med Inform Decis Mak; 2020 Sep; 20(1):225. PubMed ID: 32933515 [TBL] [Abstract][Full Text] [Related]
12. MULTI-MODAL DATA FUSION SCHEMES FOR INTEGRATED CLASSIFICATION OF IMAGING AND NON-IMAGING BIOMEDICAL DATA. Tiwari P; Viswanath S; Lee G; Madabhushi A Proc IEEE Int Symp Biomed Imaging; 2011; 2011():165-168. PubMed ID: 25705325 [TBL] [Abstract][Full Text] [Related]
13. PAGE-Net: Interpretable and Integrative Deep Learning for Survival Analysis Using Histopathological Images and Genomic Data. Hao J; Kosaraju SC; Tsaku NZ; Song DH; Kang M Pac Symp Biocomput; 2020; 25():355-366. PubMed ID: 31797610 [TBL] [Abstract][Full Text] [Related]
14. Multiscale integration of -omic, imaging, and clinical data in biomedical informatics. Phan JH; Quo CF; Cheng C; Wang MD IEEE Rev Biomed Eng; 2012; 5():74-87. PubMed ID: 23231990 [TBL] [Abstract][Full Text] [Related]
16. Deep multi-modal fusion network with gated unit for breast cancer survival prediction. Yuan H; Xu H Comput Methods Biomech Biomed Engin; 2024 May; 27(7):883-896. PubMed ID: 37166185 [TBL] [Abstract][Full Text] [Related]
17. A denoised multi-omics integration framework for cancer subtype classification and survival prediction. Pang J; Liang B; Ding R; Yan Q; Chen R; Xu J Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37594302 [TBL] [Abstract][Full Text] [Related]
18. Integrative Models of Histopathological Image Features and Omics Data Predict Survival in Head and Neck Squamous Cell Carcinoma. Zeng H; Chen L; Huang Y; Luo Y; Ma X Front Cell Dev Biol; 2020; 8():553099. PubMed ID: 33195188 [TBL] [Abstract][Full Text] [Related]
19. Integrative Analysis of Pathological Images and Multi-Dimensional Genomic Data for Early-Stage Cancer Prognosis. Shao W; Han Z; Cheng J; Cheng L; Wang T; Sun L; Lu Z; Zhang J; Zhang D; Huang K IEEE Trans Med Imaging; 2020 Jan; 39(1):99-110. PubMed ID: 31170067 [TBL] [Abstract][Full Text] [Related]
20. Multi-View Ensemble Classification of Brain Connectivity Images for Neurodegeneration Type Discrimination. Fratello M; Caiazzo G; Trojsi F; Russo A; Tedeschi G; Tagliaferri R; Esposito F Neuroinformatics; 2017 Apr; 15(2):199-213. PubMed ID: 28210983 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]