BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

340 related articles for article (PubMed ID: 34826934)

  • 21. Ethanol mediated As(III) adsorption onto Zn-loaded pinecone biochar: Experimental investigation, modeling, and optimization using hybrid artificial neural network-genetic algorithm approach.
    Zafar M; Van Vinh N; Behera SK; Park HS
    J Environ Sci (China); 2017 Apr; 54():114-125. PubMed ID: 28391919
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Artificial neural networks modeling for lead removal from aqueous solutions using iron oxide nanocomposites from bio-waste mass.
    Narayana PL; Maurya AK; Wang XS; Harsha MR; Srikanth O; Alnuaim AA; Hatamleh WA; Hatamleh AA; Cho KK; Paturi UMR; Reddy NS
    Environ Res; 2021 Aug; 199():111370. PubMed ID: 34043971
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Magnesium Oxide Embedded Nitrogen Self-Doped Biochar Composites: Fast and High-Efficiency Adsorption of Heavy Metals in an Aqueous Solution.
    Ling LL; Liu WJ; Zhang S; Jiang H
    Environ Sci Technol; 2017 Sep; 51(17):10081-10089. PubMed ID: 28753301
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Artificial neural network (ANN) approach for modeling of Pb(II) adsorption from aqueous solution by Antep pistachio (Pistacia Vera L.) shells.
    Yetilmezsoy K; Demirel S
    J Hazard Mater; 2008 May; 153(3):1288-300. PubMed ID: 17980484
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Artificial neural network-genetic algorithm based optimization for the adsorption of methylene blue and brilliant green from aqueous solution by graphite oxide nanoparticle.
    Ghaedi M; Zeinali N; Ghaedi AM; Teimuori M; Tashkhourian J
    Spectrochim Acta A Mol Biomol Spectrosc; 2014 May; 125():264-77. PubMed ID: 24556135
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Modeling and optimization by particle swarm embedded neural network for adsorption of zinc (II) by palm kernel shell based activated carbon from aqueous environment.
    Karri RR; Sahu JN
    J Environ Manage; 2018 Jan; 206():178-191. PubMed ID: 29065359
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Predictive modeling of copper (II) adsorption from aqueous solutions by sawdust: a comparative analysis of adaptive neuro-fuzzy interference system (ANFIS) and artificial neural network (ANN) approaches.
    Claude BJ; Onyango MS
    J Environ Sci Health A Tox Hazard Subst Environ Eng; 2024; 59(4):172-179. PubMed ID: 38613163
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Artificial neural network modelling for biodecolorization of Basic Violet 03 from aqueous solution by biochar derived from agro-bio waste of groundnut hull: Kinetics and thermodynamics.
    Praveen S; Jegan J; Pushpa TB; Gokulan R
    Chemosphere; 2021 Aug; 276():130191. PubMed ID: 34088088
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Application of kernel extreme learning machine and Kriging model in prediction of heavy metals removal by biochar.
    Zhao Y; Li Y; Fan D; Song J; Yang F
    Bioresour Technol; 2021 Jun; 329():124876. PubMed ID: 33640697
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Cefixime removal via WO
    Sheikhmohammadi A; Alamgholiloo H; Golaki M; Khakzad P; Asgari E; Rahimlu F
    Sci Rep; 2024 Jun; 14(1):13840. PubMed ID: 38879660
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Modeling of Cu(II) Adsorption from an Aqueous Solution Using an Artificial Neural Network (ANN).
    Khan T; Binti Abd Manan TS; Isa MH; Ghanim AAJ; Beddu S; Jusoh H; Iqbal MS; Ayele GT; Jami MS
    Molecules; 2020 Jul; 25(14):. PubMed ID: 32708928
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Stability of biochar derived from banana peel through pyrolysis as alternative source of nutrient in soil: feedforward neural network modelling study.
    Bong HK; Selvarajoo A; Arumugasamy SK
    Environ Monit Assess; 2022 Jan; 194(2):70. PubMed ID: 34994870
    [TBL] [Abstract][Full Text] [Related]  

  • 33. The modelling of lead removal from water by deep eutectic solvents functionalized CNTs: artificial neural network (ANN) approach.
    Fiyadh SS; AlSaadi MA; AlOmar MK; Fayaed SS; Hama AR; Bee S; El-Shafie A
    Water Sci Technol; 2017 Nov; 76(9-10):2413-2426. PubMed ID: 29144299
    [TBL] [Abstract][Full Text] [Related]  

  • 34. A hybrid artificial neural network and particle swarm optimization for prediction of removal of hazardous dye brilliant green from aqueous solution using zinc sulfide nanoparticle loaded on activated carbon.
    Ghaedi M; Ansari A; Bahari F; Ghaedi AM; Vafaei A
    Spectrochim Acta A Mol Biomol Spectrosc; 2015 Feb; 137():1004-15. PubMed ID: 25286113
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Machine learning in the evaluation and prediction models of biochar application: A review.
    Chen MW; Chang MS; Mao Y; Hu S; Kung CC
    Sci Prog; 2023; 106(1):368504221148842. PubMed ID: 36628421
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Artificial intelligence (AI) applications in adsorption of heavy metals using modified biochar.
    Lakshmi D; Akhil D; Kartik A; Gopinath KP; Arun J; Bhatnagar A; Rinklebe J; Kim W; Muthusamy G
    Sci Total Environ; 2021 Dec; 801():149623. PubMed ID: 34425447
    [TBL] [Abstract][Full Text] [Related]  

  • 37. The use of artificial neural network for modelling of phycoremediation of toxic elements As(III) and As(V) from wastewater using Botryococcus braunii.
    Podder MS; Majumder CB
    Spectrochim Acta A Mol Biomol Spectrosc; 2016 Feb; 155():130-45. PubMed ID: 26615452
    [TBL] [Abstract][Full Text] [Related]  

  • 38. The adsorptive removal of As (III) using biomass of arsenic resistant Bacillus thuringiensis strain WS3: Characteristics and modelling studies.
    Altowayti WAH; Algaifi HA; Bakar SA; Shahir S
    Ecotoxicol Environ Saf; 2019 May; 172():176-185. PubMed ID: 30708229
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Modeling of Remora Optimization with Deep Learning Enabled Heavy Metal Sorption Efficiency Prediction onto Biochar.
    Almalawi A; Khan AI; Alqurashi F; Abushark YB; Alam MM; Qaiyum S
    Chemosphere; 2022 Sep; 303(Pt 2):135065. PubMed ID: 35618070
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Memristive Neural Networks for Predicting Seizure Activity.
    Gerasimova SA; Lebedeva AV; Gromov NV; Malkov AE; Fedulina АА; Levanova TA; Pisarchik AN
    Sovrem Tekhnologii Med; 2023; 15(4):30-38. PubMed ID: 38434190
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 17.