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 *

184 related articles for article (PubMed ID: 35607472)

  • 1. A Statistical Prediction Model for Healthcare and Landslide Sensitivity Evaluation in Coal Mining Subsidence Area.
    Ge R; Lv Y; Tao W
    Comput Intell Neurosci; 2022; 2022():1805689. PubMed ID: 35607472
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Landslide Susceptibility Evaluation of Machine Learning Based on Information Volume and Frequency Ratio: A Case Study of Weixin County, China.
    He W; Chen G; Zhao J; Lin Y; Qin B; Yao W; Cao Q
    Sensors (Basel); 2023 Feb; 23(5):. PubMed ID: 36904752
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Zonation of Landslide Susceptibility in Ruijin, Jiangxi, China.
    Zhou X; Wu W; Lin Z; Zhang G; Chen R; Song Y; Wang Z; Lang T; Qin Y; Ou P; Huangfu W; Zhang Y; Xie L; Huang X; Fu X; Li J; Jiang J; Zhang M; Liu Y; Peng S; Shao C; Bai Y; Zhang X; Liu X; Liu W
    Int J Environ Res Public Health; 2021 May; 18(11):. PubMed ID: 34072874
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Evaluation of landslides susceptibility in Southeastern Tibet considering seismic sensitivity.
    Yeqi Z; Yonggang G; Guowen W; Shengjie W
    Heliyon; 2024 Sep; 10(18):e36800. PubMed ID: 39309935
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Exploring machine learning and statistical approach techniques for landslide susceptibility mapping in Siwalik Himalayan Region using geospatial technology.
    Saha A; Tripathi L; Villuri VGK; Bhardwaj A
    Environ Sci Pollut Res Int; 2024 Feb; 31(7):10443-10459. PubMed ID: 38198087
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Comparison of Random Forest Model and Frequency Ratio Model for Landslide Susceptibility Mapping (LSM) in Yunyang County (Chongqing, China).
    Wang Y; Sun D; Wen H; Zhang H; Zhang F
    Int J Environ Res Public Health; 2020 Jun; 17(12):. PubMed ID: 32545618
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Insights into geospatial heterogeneity of landslide susceptibility based on the SHAP-XGBoost model.
    Zhang J; Ma X; Zhang J; Sun D; Zhou X; Mi C; Wen H
    J Environ Manage; 2023 Apr; 332():117357. PubMed ID: 36731409
    [TBL] [Abstract][Full Text] [Related]  

  • 8. GIS-based multicriteria decision analysis for settlement areas: a case study in Canik.
    Kilicoglu C
    Environ Sci Pollut Res Int; 2022 May; 29(24):35746-35759. PubMed ID: 35060034
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method.
    Arca D; Kutoğlu HŞ; Becek K
    Environ Monit Assess; 2018 Nov; 190(12):725. PubMed ID: 30430322
    [TBL] [Abstract][Full Text] [Related]  

  • 10. GIS-based landslide susceptibility mapping using heuristic and bivariate statistical methods for Iva Valley and environs Southeast Nigeria.
    Ozioko OH; Igwe O
    Environ Monit Assess; 2020 Jan; 192(2):119. PubMed ID: 31950278
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Research on landslide susceptibility prediction model based on LSTM-RF-MDBN.
    Yang X; Fan X; Wang K; Zhou Z
    Environ Sci Pollut Res Int; 2024 Jan; 31(1):1504-1516. PubMed ID: 38041734
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Comparing probabilistic and statistical methods in landslide susceptibility modeling in Rwanda/Centre-Eastern Africa.
    Nsengiyumva JB; Luo G; Amanambu AC; Mind'je R; Habiyaremye G; Karamage F; Ochege FU; Mupenzi C
    Sci Total Environ; 2019 Apr; 659():1457-1472. PubMed ID: 31096356
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Evaluation of Landslide Susceptibility Based on CF-SVM in Nujiang Prefecture.
    Li Y; Deng X; Ji P; Yang Y; Jiang W; Zhao Z
    Int J Environ Res Public Health; 2022 Oct; 19(21):. PubMed ID: 36361126
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Optimization of Causative Factors for Landslide Susceptibility Evaluation Using Remote Sensing and GIS Data in Parts of Niigata, Japan.
    Dou J; Tien Bui D; Yunus AP; Jia K; Song X; Revhaug I; Xia H; Zhu Z
    PLoS One; 2015; 10(7):e0133262. PubMed ID: 26214691
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Land use change and landslide characteristics analysis for community-based disaster mitigation.
    Chen CY; Huang WL
    Environ Monit Assess; 2013 May; 185(5):4125-39. PubMed ID: 22961329
    [TBL] [Abstract][Full Text] [Related]  

  • 16. GIS-based data-driven bivariate statistical models for landslide susceptibility prediction in Upper Tista Basin, India.
    Das J; Saha P; Mitra R; Alam A; Kamruzzaman M
    Heliyon; 2023 May; 9(5):e16186. PubMed ID: 37234665
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Optimizing the Predictive Ability of Machine Learning Methods for Landslide Susceptibility Mapping Using SMOTE for Lishui City in Zhejiang Province, China.
    Wang Y; Wu X; Chen Z; Ren F; Feng L; Du Q
    Int J Environ Res Public Health; 2019 Jan; 16(3):. PubMed ID: 30696105
    [TBL] [Abstract][Full Text] [Related]  

  • 18. GIS-based landslide susceptibility mapping in the Longmen Mountain area (China) using three different machine learning algorithms and their comparison.
    Huang Z; Peng L; Li S; Liu Y; Zhou S
    Environ Sci Pollut Res Int; 2023 Aug; 30(38):88612-88626. PubMed ID: 37440134
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Landslide susceptibility assessment using the Weight of Evidence method: A case study in Xunyang area, China.
    Cao Y; Wei X; Fan W; Nan Y; Xiong W; Zhang S
    PLoS One; 2021; 16(1):e0245668. PubMed ID: 33493200
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Landslide Susceptibility Assessment Using Spatial Multi-Criteria Evaluation Model in Rwanda.
    Nsengiyumva JB; Luo G; Nahayo L; Huang X; Cai P
    Int J Environ Res Public Health; 2018 Jan; 15(2):. PubMed ID: 29385096
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.