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 *

187 related articles for article (PubMed ID: 34716368)

  • 61. Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning.
    Dou J; Yunus AP; Merghadi A; Shirzadi A; Nguyen H; Hussain Y; Avtar R; Chen Y; Pham BT; Yamagishi H
    Sci Total Environ; 2020 Jun; 720():137320. PubMed ID: 32325551
    [TBL] [Abstract][Full Text] [Related]  

  • 62. Automated Landslide-Risk Prediction Using Web GIS and Machine Learning Models.
    Tengtrairat N; Woo WL; Parathai P; Aryupong C; Jitsangiam P; Rinchumphu D
    Sensors (Basel); 2021 Jul; 21(13):. PubMed ID: 34283153
    [TBL] [Abstract][Full Text] [Related]  

  • 63. A mechanistic approach to include climate change and unplanned urban sprawl in landslide susceptibility maps.
    Bozzolan E; Holcombe EA; Pianosi F; Marchesini I; Alvioli M; Wagener T
    Sci Total Environ; 2023 Feb; 858(Pt 1):159412. PubMed ID: 36244475
    [TBL] [Abstract][Full Text] [Related]  

  • 64. SAR and optical images correlation illuminates post-seismic landslide motion after the Mw 7.8 Gorkha earthquake (Nepal).
    Lacroix P; Gavillon T; Bouchant C; Lavé J; Mugnier JL; Dhungel S; Vernier F
    Sci Rep; 2022 Apr; 12(1):6266. PubMed ID: 35428776
    [TBL] [Abstract][Full Text] [Related]  

  • 65. Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China.
    Wang Z; Ma C; Qiu Y; Xiong H; Li M
    Int J Environ Res Public Health; 2022 Aug; 19(15):. PubMed ID: 35954770
    [TBL] [Abstract][Full Text] [Related]  

  • 66. The importance of input data on landslide susceptibility mapping.
    Gaidzik K; Ramírez-Herrera MT
    Sci Rep; 2021 Sep; 11(1):19334. PubMed ID: 34588548
    [TBL] [Abstract][Full Text] [Related]  

  • 67. Landslide susceptibility mapping using the statistical method of Information Value: A study case in Ribeirão dos Macacos basin, Minas Gerais, Brazil.
    Rosa ML; Sobreira FG; Barella CF
    An Acad Bras Cienc; 2021; 93(1):e20180897. PubMed ID: 33470291
    [TBL] [Abstract][Full Text] [Related]  

  • 68. Mapping the susceptibility of persons with disabilities to landslides in a highland landscape of Bushika Sub County, Mount Elgon, Eastern Uganda.
    Ssennoga M; Mugagga F; Nadhomi DL; Kisira Y
    Jamba; 2022; 14(1):1266. PubMed ID: 35774472
    [TBL] [Abstract][Full Text] [Related]  

  • 69. Multi-hazard probability assessment and mapping in Iran.
    Pourghasemi HR; Gayen A; Panahi M; Rezaie F; Blaschke T
    Sci Total Environ; 2019 Nov; 692():556-571. PubMed ID: 31351297
    [TBL] [Abstract][Full Text] [Related]  

  • 70. Valuable Clues for DCNN-Based Landslide Detection from a Comparative Assessment in the Wenchuan Earthquake Area.
    Li C; Yi B; Gao P; Li H; Sun J; Chen X; Zhong C
    Sensors (Basel); 2021 Jul; 21(15):. PubMed ID: 34372428
    [TBL] [Abstract][Full Text] [Related]  

  • 71. 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]  

  • 72. An essential update on the inventory of landslides triggered by the Jiuzhaigou Mw6.5 earthquake in China on 8 August 2017, with their spatial distribution analyses.
    Sun J; Shao X; Feng L; Xu C; Huang Y; Yang W
    Heliyon; 2024 Jan; 10(2):e24787. PubMed ID: 38312686
    [TBL] [Abstract][Full Text] [Related]  

  • 73. Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China.
    Chen W; Peng J; Hong H; Shahabi H; Pradhan B; Liu J; Zhu AX; Pei X; Duan Z
    Sci Total Environ; 2018 Jun; 626():1121-1135. PubMed ID: 29898519
    [TBL] [Abstract][Full Text] [Related]  

  • 74. Analysis of landslide explicative factors and susceptibility mapping in an andean context: The case of Azuay province (Ecuador).
    Cobos-Mora SL; Rodriguez-Galiano V; Lima A
    Heliyon; 2023 Sep; 9(9):e20170. PubMed ID: 37809729
    [TBL] [Abstract][Full Text] [Related]  

  • 75. Co-seismic landslide topographic analysis based on multi-temporal DEM-A case study of the Wenchuan earthquake.
    Ren Z; Zhang Z; Dai F; Yin J; Zhang H
    Springerplus; 2013; 2(1):544. PubMed ID: 24171155
    [TBL] [Abstract][Full Text] [Related]  

  • 76. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis.
    Feizizadeh B; Jankowski P; Blaschke T
    Comput Geosci; 2014 Mar; 64():81-95. PubMed ID: 25843987
    [TBL] [Abstract][Full Text] [Related]  

  • 77. Integrating Remote Sensing Data with Directional Two- Dimensional Wavelet Analysis and Open Geospatial Techniques for Efficient Disaster Monitoring and Management.
    Lin YB; Lin YP; Deng DP; Chen KW
    Sensors (Basel); 2008 Feb; 8(2):1070-1089. PubMed ID: 27879753
    [TBL] [Abstract][Full Text] [Related]  

  • 78. Identification of precipitation trend and landslide susceptibility analysis in Miandoab County using MATLAB.
    Rezapour Andabili N; Safaripour M
    Environ Monit Assess; 2022 Jun; 194(7):472. PubMed ID: 35655104
    [TBL] [Abstract][Full Text] [Related]  

  • 79. The influence of land use change on landslide susceptibility zonation: the Briga catchment test site (Messina, Italy).
    Reichenbach P; Busca C; Mondini AC; Rossi M
    Environ Manage; 2014 Dec; 54(6):1372-84. PubMed ID: 25164982
    [TBL] [Abstract][Full Text] [Related]  

  • 80. Mine landslide susceptibility assessment using IVM, ANN and SVM models considering the contribution of affecting factors.
    Luo X; Lin F; Zhu S; Yu M; Zhang Z; Meng L; Peng J
    PLoS One; 2019; 14(4):e0215134. PubMed ID: 30973936
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 10.