Literature DB >> 19716414

Advantages of neurofuzzy logic against conventional experimental design and statistical analysis in studying and developing direct compression formulations.

Mariana Landín1, R C Rowe, P York.   

Abstract

This study has investigated the utility and potential advantages of an artificial intelligence technology - neurofuzzy logic - as a modeling tool to study direct compression formulations. The modeling performance was compare with traditional statistical analysis. From results it can be stated that the normalized error obtained from neurofuzzy logic was lower. Compared to the multiple regression analysis neurofuzzy logic showed higher accuracy in prediction for the five outputs studied. Rule sets generated by neurofuzzy logic are completely in agreement with the findings based on statistical analysis and advantageously generate understandable and reusable knowledge. Neurofuzzy logic is easy and rapid to apply and outcomes provided knowledge not revealed via statistical analysis.

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Year:  2009        PMID: 19716414     DOI: 10.1016/j.ejps.2009.08.004

Source DB:  PubMed          Journal:  Eur J Pharm Sci        ISSN: 0928-0987            Impact factor:   4.384


  14 in total

1.  Strengths of artificial neural networks in modeling complex plant processes.

Authors:  Jorge Gago; Mariana Landín; Pedro Pablo Gallego
Journal:  Plant Signal Behav       Date:  2010-06-01

2.  Finding key nanoprecipitation variables for achieving uniform polymeric nanoparticles using neurofuzzy logic technology.

Authors:  Miguel O Jara; Johanna Catalan-Figueroa; Mariana Landin; Javier O Morales
Journal:  Drug Deliv Transl Res       Date:  2018-12       Impact factor: 4.617

3.  Artificial Neural Networks Elucidated the Essential Role of Mineral Nutrients versus Vitamins and Plant Growth Regulators in Achieving Healthy Micropropagated Plants.

Authors:  Tomás A Arteta; Radhia Hameg; Mariana Landin; Pedro P Gallego; M Esther Barreal
Journal:  Plants (Basel)       Date:  2022-05-11

4.  Artificial neural network-based model for the prediction of optimal growth and culture conditions for maximum biomass accumulation in multiple shoot cultures of Centella asiatica.

Authors:  Archana Prasad; Om Prakash; Shakti Mehrotra; Feroz Khan; Ajay Kumar Mathur; Archana Mathur
Journal:  Protoplasma       Date:  2016-04-11       Impact factor: 3.356

5.  Computer modeling assisted design of monodisperse PLGA microspheres with controlled porosity affords zero order release of an encapsulated macromolecule for 3 months.

Authors:  Filis Kazazi-Hyseni; Mariana Landin; Audrey Lathuile; Gert J Veldhuis; Sima Rahimian; Wim E Hennink; Robbert Jan Kok; Cornelus F van Nostrum
Journal:  Pharm Res       Date:  2014-05-14       Impact factor: 4.200

6.  Mycobacterium avium subsp. paratuberculosis (Map) Fatty Acids Profile Is Strain-Dependent and Changes Upon Host Macrophages Infection.

Authors:  Marta Alonso-Hearn; Naiara Abendaño; Maria A Ruvira; Rosa Aznar; Mariana Landin; Ramon A Juste
Journal:  Front Cell Infect Microbiol       Date:  2017-03-21       Impact factor: 5.293

7.  Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

Authors:  Lakshmi Pathak; Vineeta Singh; Ram Niwas; Khwaja Osama; Saif Khan; Shafiul Haque; C K M Tripathi; B N Mishra
Journal:  PLoS One       Date:  2015-09-14       Impact factor: 3.240

8.  Isotretinoin oil-based capsule formulation optimization.

Authors:  Pi-Ju Tsai; Chi-Te Huang; Chen-Chou Lee; Chi-Lin Li; Yaw-Bin Huang; Yi-Hung Tsai; Pao-Chu Wu
Journal:  ScientificWorldJournal       Date:  2013-08-26

9.  Modeling the effects of light and sucrose on in vitro propagated plants: a multiscale system analysis using artificial intelligence technology.

Authors:  Jorge Gago; Lourdes Martínez-Núñez; Mariana Landín; Jaume Flexas; Pedro P Gallego
Journal:  PLoS One       Date:  2014-01-20       Impact factor: 3.240

Review 10.  The Future of Pharmaceutical Manufacturing Sciences.

Authors:  Jukka Rantanen; Johannes Khinast
Journal:  J Pharm Sci       Date:  2015-08-17       Impact factor: 3.534

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