BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

122 related articles for article (PubMed ID: 38657466)

  • 1. Deep learning and machine learning approaches to classify stomach distant metastatic tumors using DNA methylation profiles.
    Shi J; Chen Y; Wang Y
    Comput Biol Med; 2024 Jun; 175():108496. PubMed ID: 38657466
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep Learning and Machine Learning with Grid Search to Predict Later Occurrence of Breast Cancer Metastasis Using Clinical Data.
    Jiang X; Xu C
    J Clin Med; 2022 Sep; 11(19):. PubMed ID: 36233640
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine Learning Approaches to Classify Primary and Metastatic Cancers Using Tissue of Origin-Based DNA Methylation Profiles.
    Modhukur V; Sharma S; Mondal M; Lawarde A; Kask K; Sharma R; Salumets A
    Cancers (Basel); 2021 Jul; 13(15):. PubMed ID: 34359669
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Integrative analysis of DNA methylation and gene expression through machine learning identifies stomach cancer diagnostic and prognostic biomarkers.
    Hosseini M; Lotfi-Shahreza M; Nikpour P
    J Cell Mol Med; 2023 Mar; 27(5):714-726. PubMed ID: 36779430
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Identification of Biomarkers for Predicting Lymph Node Metastasis of Stomach Cancer Using Clinical DNA Methylation Data.
    Wu J; Xiao Y; Xia C; Yang F; Li H; Shao Z; Lin Z; Zhao X
    Dis Markers; 2017; 2017():5745724. PubMed ID: 28951630
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Machine learning and deep learning methods that use omics data for metastasis prediction.
    Albaradei S; Thafar M; Alsaedi A; Van Neste C; Gojobori T; Essack M; Gao X
    Comput Struct Biotechnol J; 2021; 19():5008-5018. PubMed ID: 34589181
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Application of interpretable machine learning algorithms to predict distant metastasis in ovarian clear cell carcinoma.
    Guo QH; Xie FC; Zhong FM; Wen W; Zhang XR; Yu XJ; Wang XL; Huang B; Li LP; Wang XZ
    Cancer Med; 2024 Apr; 13(7):e7161. PubMed ID: 38613173
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Methylation of the claudin‑3 promoter predicts the prognosis of advanced gastric adenocarcinoma.
    Zhang Z; Yu W; Chen S; Chen Y; Chen L; Zhang S
    Oncol Rep; 2018 Jul; 40(1):49-60. PubMed ID: 29749528
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Screening lncRNAs with diagnostic and prognostic value for human stomach adenocarcinoma based on machine learning and mRNA-lncRNA co-expression network analysis.
    Li Q; Liu X; Gu J; Zhu J; Wei Z; Huang H
    Mol Genet Genomic Med; 2020 Nov; 8(11):e1512. PubMed ID: 33002344
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Predicting metastasis in gastric cancer patients: machine learning-based approaches.
    Talebi A; Celis-Morales CA; Borumandnia N; Abbasi S; Pourhoseingholi MA; Akbari A; Yousefi J
    Sci Rep; 2023 Mar; 13(1):4163. PubMed ID: 36914697
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Epigenetic subgroups of esophageal and gastric adenocarcinoma with differential GATA5 DNA methylation associated with clinical and lifestyle factors.
    Wang X; Kang GH; Campan M; Weisenberger DJ; Long TI; Cozen W; Bernstein L; Wu AH; Siegmund KD; Shibata D; Laird PW
    PLoS One; 2011; 6(10):e25985. PubMed ID: 22028801
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A hybrid metaheuristic-deep learning technique for the pan-classification of cancer based on DNA methylation.
    Eissa NS; Khairuddin U; Yusof R
    BMC Bioinformatics; 2022 Jul; 23(1):273. PubMed ID: 35818034
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Predicting Breast Cancer Based on Optimized Deep Learning Approach.
    Saleh H; Abd-El Ghany SF; Alyami H; Alosaimi W
    Comput Intell Neurosci; 2022; 2022():1820777. PubMed ID: 35345799
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Detection of RASSF1A promoter hypermethylation in serum from gastric and colorectal adenocarcinoma patients.
    Wang YC; Yu ZH; Liu C; Xu LZ; Yu W; Lu J; Zhu RM; Li GL; Xia XY; Wei XW; Ji HZ; Lu H; Gao Y; Gao WM; Chen LB
    World J Gastroenterol; 2008 May; 14(19):3074-80. PubMed ID: 18494062
    [TBL] [Abstract][Full Text] [Related]  

  • 15. CoAID-DEEP: An Optimized Intelligent Framework for Automated Detecting COVID-19 Misleading Information on Twitter.
    Abdelminaam DS; Ismail FH; Taha M; Taha A; Houssein EH; Nabil A
    IEEE Access; 2021; 9():27840-27867. PubMed ID: 34786308
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Machine learning-based prediction model for distant metastasis of breast cancer.
    Duan H; Zhang Y; Qiu H; Fu X; Liu C; Zang X; Xu A; Wu Z; Li X; Zhang Q; Zhang Z; Cui F
    Comput Biol Med; 2024 Feb; 169():107943. PubMed ID: 38211382
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Prediction and Diagnosis of Breast Cancer Using Machine and Modern Deep Learning Models.
    Devi S; Kaul Ghanekar R; Pande JA; Dumbre D; Chavan R; Gupta H
    Asian Pac J Cancer Prev; 2024 Mar; 25(3):1077-1085. PubMed ID: 38546090
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A Group of miRNA as Candidates for Prognostic Biomarkers of Gastric Cancer Metastasis.
    Kipkeeva FM; Muzaffarova ТА; Nikulin MP; Apanovich PV; Narimanov MN; Malikhova OA; Kushlinskii NE; Stilidi IS; Karpukhin AV
    Bull Exp Biol Med; 2020 May; 169(1):77-80. PubMed ID: 32488785
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Machine learning random forest for predicting oncosomatic variant NGS analysis.
    Pellegrino E; Jacques C; Beaufils N; Nanni I; Carlioz A; Metellus P; Ouafik L
    Sci Rep; 2021 Nov; 11(1):21820. PubMed ID: 34750410
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.