BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

137 related articles for article (PubMed ID: 36586442)

  • 1. Novel machine learning algorithms to predict the groundwater vulnerability index to nitrate pollution at two levels of modeling.
    Elzain HE; Chung SY; Venkatramanan S; Selvam S; Ahemd HA; Seo YK; Bhuyan MS; Yassin MA
    Chemosphere; 2023 Feb; 314():137671. PubMed ID: 36586442
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Delimitation of groundwater zones under contamination risk using a bagged ensemble of optimized DRASTIC frameworks.
    Barzegar R; Asghari Moghaddam A; Adamowski J; Nazemi AH
    Environ Sci Pollut Res Int; 2019 Mar; 26(8):8325-8339. PubMed ID: 30706265
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Comparative study of machine learning models for evaluating groundwater vulnerability to nitrate contamination.
    Elzain HE; Chung SY; Senapathi V; Sekar S; Lee SY; Roy PD; Hassan A; Sabarathinam C
    Ecotoxicol Environ Saf; 2022 Jan; 229():113061. PubMed ID: 34902776
    [TBL] [Abstract][Full Text] [Related]  

  • 4. An innovative approach for predicting groundwater TDS using optimized ensemble machine learning algorithms at two levels of modeling strategy.
    Elzain HE; Abdalla O; A Ahmed H; Kacimov A; Al-Maktoumi A; Al-Higgi K; Abdallah M; Yassin MA; Senapathi V
    J Environ Manage; 2024 Feb; 351():119896. PubMed ID: 38171121
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Improving groundwater nitrate concentration prediction using local ensemble of machine learning models.
    Mahboobi H; Shakiba A; Mirbagheri B
    J Environ Manage; 2023 Nov; 345():118782. PubMed ID: 37597371
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Geostatistical estimates of groundwater nitrate-nitrogen concentrations with spatial auxiliary information on DRASTIC-LU-based aquifer contamination vulnerability.
    Jang CS
    Environ Sci Pollut Res Int; 2023 Jul; 30(33):81113-81130. PubMed ID: 37314554
    [TBL] [Abstract][Full Text] [Related]  

  • 7. ANFIS-MOA models for the assessment of groundwater contamination vulnerability in a nitrate contaminated area.
    Elzain HE; Chung SY; Park KH; Senapathi V; Sekar S; Sabarathinam C; Hassan M
    J Environ Manage; 2021 May; 286():112162. PubMed ID: 33636625
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Mapping groundwater contamination risk of multiple aquifers using multi-model ensemble of machine learning algorithms.
    Barzegar R; Moghaddam AA; Deo R; Fijani E; Tziritis E
    Sci Total Environ; 2018 Apr; 621():697-712. PubMed ID: 29197289
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predictive modeling of groundwater nitrate pollution using Random Forest and multisource variables related to intrinsic and specific vulnerability: a case study in an agricultural setting (Southern Spain).
    Rodriguez-Galiano V; Mendes MP; Garcia-Soldado MJ; Chica-Olmo M; Ribeiro L
    Sci Total Environ; 2014 Apr; 476-477():189-206. PubMed ID: 24463255
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Susceptibility Assessment of Groundwater Nitrate Contamination Using an Ensemble Machine Learning Approach.
    Hosseini FS; Choubin B; Bagheri-Gavkosh M; Karimi O; Taromideh F; Mako C
    Ground Water; 2023; 61(4):510-516. PubMed ID: 36127852
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Modified-DRASTIC, modified-SINTACS and SI methods for groundwater vulnerability assessment in the southern Tehran aquifer.
    Noori R; Ghahremanzadeh H; Kløve B; Adamowski JF; Baghvand A
    J Environ Sci Health A Tox Hazard Subst Environ Eng; 2019; 54(1):89-100. PubMed ID: 30596317
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Would delineation of nitrate vulnerable zones be improved by introducing a new parameter representing the risk associated with soil permeability in the Land Use-Intrinsic Vulnerability Procedure?
    Arauzo M; Valladolid M; Andries DM
    Sci Total Environ; 2022 Sep; 840():156654. PubMed ID: 35700776
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Modeling of aquifer vulnerability index using deep learning neural networks coupling with optimization algorithms.
    Elzain HE; Chung SY; Senapathi V; Sekar S; Park N; Mahmoud AA
    Environ Sci Pollut Res Int; 2021 Oct; 28(40):57030-57045. PubMed ID: 34081280
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Modelling hydrogeological parameters to assess groundwater pollution and vulnerability in Kashan aquifer: Novel calibration-validation of multivariate statistical methods and human health risk considerations.
    Samadi J
    Environ Res; 2022 Aug; 211():113028. PubMed ID: 35283077
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Assessment of the risks of N-loss to groundwater from data on N-balance surplus in Spanish crops: An empirical basis to identify Nitrate Vulnerable Zones.
    Arauzo M; García G; Valladolid M
    Sci Total Environ; 2019 Dec; 696():133713. PubMed ID: 31461691
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Implementation and evaluation of different techniques to modify DRASTIC method for groundwater vulnerability assessment: a case study from Bouficha aquifer, Tunisia.
    Siarkos I; Arfaoui M; Tzoraki O; Zammouri M; Hamzaoui-Azaza F
    Environ Sci Pollut Res Int; 2023 Aug; 30(38):89459-89478. PubMed ID: 37453015
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Predictive modeling of selected trace elements in groundwater using hybrid algorithms of iterative classifier optimizer.
    Khosravi K; Barzegar R; Golkarian A; Busico G; Cuoco E; Mastrocicco M; Colombani N; Tedesco D; Ntona MM; Kazakis N
    J Contam Hydrol; 2021 Oct; 242():103849. PubMed ID: 34147829
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A fuzzy logic-based approach for groundwater vulnerability assessment.
    Nourani V; Maleki S; Najafi H; Baghanam AH
    Environ Sci Pollut Res Int; 2024 Mar; 31(12):18010-18029. PubMed ID: 36940030
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Decision-tree-model identification of nitrate pollution activities in groundwater: A combination of a dual isotope approach and chemical ions.
    Xue D; Pang F; Meng F; Wang Z; Wu W
    J Contam Hydrol; 2015 Sep; 180():25-33. PubMed ID: 26231989
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A machine learning framework for spatio-temporal vulnerability mapping of groundwaters to nitrate in a data scarce region in Lenjanat Plain, Iran.
    Jalali R; Tishehzan P; Hashemi H
    Environ Sci Pollut Res Int; 2024 Jun; 31(29):42088-42110. PubMed ID: 38862797
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.