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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

110 related articles for article (PubMed ID: 35461302)

  • 1. Colorectal cancer subtype identification from differential gene expression levels using minimalist deep learning.
    Li S; Yang Y; Wang X; Li J; Yu J; Li X; Wong KC
    BioData Min; 2022 Apr; 15(1):12. PubMed ID: 35461302
    [TBL] [Abstract][Full Text] [Related]  

  • 2. DeepCC: a novel deep learning-based framework for cancer molecular subtype classification.
    Gao F; Wang W; Tan M; Zhu L; Zhang Y; Fessler E; Vermeulen L; Wang X
    Oncogenesis; 2019 Aug; 8(9):44. PubMed ID: 31420533
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Automated exploitation of deep learning for cancer patient stratification across multiple types.
    Sun P; Fan S; Li S; Zhao Y; Lu C; Wong KC; Li X
    Bioinformatics; 2023 Nov; 39(11):. PubMed ID: 37934154
    [TBL] [Abstract][Full Text] [Related]  

  • 4. BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data.
    Guo Y; Liu S; Li Z; Shang X
    BMC Bioinformatics; 2018 Apr; 19(Suppl 5):118. PubMed ID: 29671390
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Optimizing neural networks for medical data sets: A case study on neonatal apnea prediction.
    Shirwaikar RD; Acharya U D; Makkithaya K; M S; Srivastava S; Lewis U LES
    Artif Intell Med; 2019 Jul; 98():59-76. PubMed ID: 31521253
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Molecular Subtyping of Cancer Based on Distinguishing Co-Expression Modules and Machine Learning.
    Sun P; Wu Y; Yin C; Jiang H; Xu Y; Sun H
    Front Genet; 2022; 13():866005. PubMed ID: 35586568
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A deep neural network approach to predicting clinical outcomes of neuroblastoma patients.
    Tranchevent LC; Azuaje F; Rajapakse JC
    BMC Med Genomics; 2019 Dec; 12(Suppl 8):178. PubMed ID: 31856829
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Machine learning assisted analysis of breast cancer gene expression profiles reveals novel potential prognostic biomarkers for triple-negative breast cancer.
    Thalor A; Kumar Joon H; Singh G; Roy S; Gupta D
    Comput Struct Biotechnol J; 2022; 20():1618-1631. PubMed ID: 35465161
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A laminar augmented cascading flexible neural forest model for classification of cancer subtypes based on gene expression data.
    Zhong L; Meng Q; Chen Y; Du L; Wu P
    BMC Bioinformatics; 2021 Oct; 22(1):475. PubMed ID: 34600466
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Machine Learning-Based Identification of Colon Cancer Candidate Diagnostics Genes.
    Koppad S; Basava A; Nash K; Gkoutos GV; Acharjee A
    Biology (Basel); 2022 Feb; 11(3):. PubMed ID: 35336739
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Deep Learning Feature Extraction Approach for Hematopoietic Cancer Subtype Classification.
    Park KH; Batbaatar E; Piao Y; Theera-Umpon N; Ryu KH
    Int J Environ Res Public Health; 2021 Feb; 18(4):. PubMed ID: 33672300
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Weighted dimensionality reduction and robust Gaussian mixture model based cancer patient subtyping from gene expression data.
    Rafique O; Mir AH
    J Biomed Inform; 2020 Dec; 112():103620. PubMed ID: 33188907
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Identification of infectious disease-associated host genes using machine learning techniques.
    Barman RK; Mukhopadhyay A; Maulik U; Das S
    BMC Bioinformatics; 2019 Dec; 20(1):736. PubMed ID: 31881961
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data.
    Koutsoukas A; Monaghan KJ; Li X; Huan J
    J Cheminform; 2017 Jun; 9(1):42. PubMed ID: 29086090
    [TBL] [Abstract][Full Text] [Related]  

  • 15. ForestSubtype: a cancer subtype identifying approach based on high-dimensional genomic data and a parallel random forest.
    Luo J; Feng Y; Wu X; Li R; Shi J; Chang W; Wang J
    BMC Bioinformatics; 2023 Jul; 24(1):289. PubMed ID: 37468832
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Hubness weighted SVM ensemble for prediction of breast cancer subtypes.
    Raja Sree S; Kunthavai A
    Technol Health Care; 2022; 30(3):565-578. PubMed ID: 34397436
    [TBL] [Abstract][Full Text] [Related]  

  • 17. De novo transcriptomic subtyping of colorectal cancer liver metastases in the context of tumor heterogeneity.
    Moosavi SH; Eide PW; Eilertsen IA; Brunsell TH; Berg KCG; Røsok BI; Brudvik KW; Bjørnbeth BA; Guren MG; Nesbakken A; Lothe RA; Sveen A
    Genome Med; 2021 Sep; 13(1):143. PubMed ID: 34470666
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Identification of pan-cancer Ras pathway activation with deep learning.
    Li X; Li S; Wang Y; Zhang S; Wong KC
    Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33126245
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach.
    Liang M; Li Z; Chen T; Zeng J
    IEEE/ACM Trans Comput Biol Bioinform; 2015; 12(4):928-37. PubMed ID: 26357333
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Uncovering the prognostic gene signatures for the improvement of risk stratification in cancers by using deep learning algorithm coupled with wavelet transform.
    Zhao Y; Zhou Y; Liu Y; Hao Y; Li M; Pu X; Li C; Wen Z
    BMC Bioinformatics; 2020 May; 21(1):195. PubMed ID: 32429941
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.