메뉴 건너뛰기




Volumn 2, Issue 2, 1997, Pages 95-109

Basic concepts of Artificial Neural Networks (ANN) modeling in the application to pharmaceutical development

Author keywords

Artificial neural networks (ANN); Associating networks; Comparison of modeling techniques; Feature extracting networks; Learning algorithms; Nonadaptive networks; Pharmaceutical technology

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER ANALYSIS; COMPUTER PROGRAM; MATHEMATICAL MODEL; NERVE CELL NETWORK; PHARMACEUTICS; PRIORITY JOURNAL; RELIABILITY; STATISTICAL MODEL; SYNAPSE;

EID: 0031392564     PISSN: 10837450     EISSN: None     Source Type: Journal    
DOI: 10.3109/10837459709022615     Document Type: Article
Times cited : (81)

References (35)
  • 1
    • 0025838017 scopus 로고
    • Application of neural computing in pharmaceutical product development
    • A. S. Hussain, Y. Xuanqjang, and R. D. Johnson, Application of neural computing in pharmaceutical product development, Pharm. Res., 8:1248-1252 (1991)
    • (1991) Pharm. Res. , vol.8 , pp. 1248-1252
    • Hussain, A.S.1    Xuanqjang, Y.2    Johnson, R.D.3
  • 2
    • 0342645307 scopus 로고
    • Comparison of four different neural network training algorithms in modelling the fluidized bed granulation process
    • E. Murtoniemi, P. Merkku, and J. Yliruusi, Comparison of four different neural network training algorithms in modelling the fluidized bed granulation process. Lab. Microcomput., 12(3):69-76 (1993).
    • (1993) Lab. Microcomput. , vol.12 , Issue.3 , pp. 69-76
    • Murtoniemi, E.1    Merkku, P.2    Yliruusi, J.3
  • 3
    • 0028365967 scopus 로고
    • Application of neural computing in pharmaceutical product development: Computer aided formulation design
    • A. S. Hussain, P. Shivanand, and R. D. Johnson, Application of neural computing in pharmaceutical product development: Computer aided formulation design, Drug Dev. Ind. Pharm., 20(10): 1739-1752 (1994).
    • (1994) Drug Dev. Ind. Pharm. , vol.20 , Issue.10 , pp. 1739-1752
    • Hussain, A.S.1    Shivanand, P.2    Johnson, R.D.3
  • 4
    • 0028291936 scopus 로고
    • The advantages by the use of neural networks in modelling the fluidized bed granulation process
    • E. Murtoniemi, J. Yliruusi, P. Kinnunen, P. Merkku, and K. Leiviskä, The advantages by the use of neural networks in modelling the fluidized bed granulation process, Int. J. Pharm., 108:155-164 (1994).
    • (1994) Int. J. Pharm. , vol.108 , pp. 155-164
    • Murtoniemi, E.1    Yliruusi, J.2    Kinnunen, P.3    Merkku, P.4    Leiviskä, K.5
  • 5
    • 0028145805 scopus 로고
    • Effect of neural network topology and training end point in modelling the fluidized bed granulation process
    • E. Murtoniemi, P. Merkku, P. Kinnunen, K. Leiviskä, and J. Yliruusi, Effect of neural network topology and training end point in modelling the fluidized bed granulation process, Int. J. Pharm., 110:101-108 (1994).
    • (1994) Int. J. Pharm. , vol.110 , pp. 101-108
    • Murtoniemi, E.1    Merkku, P.2    Kinnunen, P.3    Leiviskä, K.4    Yliruusi, J.5
  • 6
    • 0028829043 scopus 로고
    • Artificial Neural network analysis of a direct compression tabletting study
    • M. Türkoglu, R. Ozarslan, and A. Sakr, Artificial Neural network analysis of a direct compression tabletting study, Eur. J. Pharm. Biopharm., 41(5):315-322 (1995).
    • (1995) Eur. J. Pharm. Biopharm. , vol.41 , Issue.5 , pp. 315-322
    • Türkoglu, M.1    Ozarslan, R.2    Sakr, A.3
  • 7
    • 0027396025 scopus 로고
    • Introduction to backpropagation neural network computation
    • R. J. Erb, Introduction to backpropagation neural network computation, Pharm. Res., 10(2):165-170 (1993).
    • (1993) Pharm. Res. , vol.10 , Issue.2 , pp. 165-170
    • Erb, R.J.1
  • 8
    • 0028816977 scopus 로고
    • Artificial neural networks: Implications for pharmaceutical sciences
    • A. S. Achanta, J. G. Kowalski, and C. T. Rhodes, Artificial neural networks: Implications for pharmaceutical sciences, Drug Dev. Ind. Pharm., 21(1):119-155 (1995).
    • (1995) Drug Dev. Ind. Pharm. , vol.21 , Issue.1 , pp. 119-155
    • Achanta, A.S.1    Kowalski, J.G.2    Rhodes, C.T.3
  • 9
    • 0023855839 scopus 로고
    • An introduction to neural computing
    • T. Kohonen, An introduction to neural computing, Neural Networks, 1:3-16 (1988).
    • (1988) Neural Networks , vol.1 , pp. 3-16
    • Kohonen, T.1
  • 10
    • 0023984443 scopus 로고
    • Neurocomputing: Picking the human brain
    • R. Hecht-Nielsen, Neurocomputing: Picking the human brain, IEEE Spectrum, 3:36-41 (1988).
    • (1988) IEEE Spectrum , vol.3 , pp. 36-41
    • Hecht-Nielsen, R.1
  • 13
    • 51249194645 scopus 로고
    • A logical calculus of the ideas immanent in nervous activity
    • W. S. McCulloch and W. Pitts, A logical calculus of the ideas immanent in nervous activity, Bull. Math. Biophys., 5:115-133 (1943).
    • (1943) Bull. Math. Biophys. , vol.5 , pp. 115-133
    • McCulloch, W.S.1    Pitts, W.2
  • 15
    • 11144273669 scopus 로고
    • The perceptron: A probabilistic model for information storage and organization in the brain
    • F. Rosenblatt, The perceptron: A probabilistic model for information storage and organization in the brain, Psychol. Rev., 65:386-408 (1958).
    • (1958) Psychol. Rev. , vol.65 , pp. 386-408
    • Rosenblatt, F.1
  • 17
    • 0020118274 scopus 로고
    • Neural networks and physical systems with emergent collective computational abilities
    • J. J. Hopfield, Neural networks and physical systems with emergent collective computational abilities, Proc. Natl. Acad. Sci. USA, 79:2554-2558 (1982).
    • (1982) Proc. Natl. Acad. Sci. USA , vol.79 , pp. 2554-2558
    • Hopfield, J.J.1
  • 18
    • 0022471098 scopus 로고
    • Learning representations by back-propagating errors
    • D. E. Rumelhart, G. E. Hinton, and R. J. Williams, Learning representations by back-propagating errors, Nature, 323:533-536 (1986).
    • (1986) Nature , vol.323 , pp. 533-536
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 20
    • 2642606610 scopus 로고
    • A neural network for nonlinear Bayesian estimation in drug therapy
    • R. Shadmehr and D. Z. D'Argenio, A neural network for nonlinear Bayesian estimation in drug therapy, Neural Comput., 2:216-225 (1990).
    • (1990) Neural Comput. , vol.2 , pp. 216-225
    • Shadmehr, R.1    D'Argenio, D.Z.2
  • 21
    • 0027052238 scopus 로고
    • Perspective in pharmacokinetics, Neural networks in pharmacodynamic modelling. Is current modelling practice of complex kinetic system at a dead end?
    • P. Veng-Pedersen and N. B. Modi, Perspective in pharmacokinetics, Neural networks in pharmacodynamic modelling. Is current modelling practice of complex kinetic system at a dead end? J. Pharmacokin. Biopharm., 20(4):397-412 (1992).
    • (1992) J. Pharmacokin. Biopharm. , vol.20 , Issue.4 , pp. 397-412
    • Veng-Pedersen, P.1    Modi, N.B.2
  • 22
    • 0027528980 scopus 로고
    • Feasibility of developing a neural network for prediction of human pharmacokinetic parameters from animal data
    • A. S. Hussain, R.D . Johnson, N. N. Vachharajani, and W. A. Ritschel, Feasibility of developing a neural network for prediction of human pharmacokinetic parameters from animal data, Pharm. Res., 10(3):466-469 (1993).
    • (1993) Pharm. Res. , vol.10 , Issue.3 , pp. 466-469
    • Hussain, A.S.1    Johnson, R.D..2    Vachharajani, N.N.3    Ritschel, W.A.4
  • 23
    • 0026332221 scopus 로고
    • Neural networks as a tool for utilizing laboratory information: Comparison with linear discriminant analysis and with classification and regression trees
    • G. Reibnegger, G. Weiss, G. Werner-Felmayer, G. Judmaier, and H. Wachter, Neural networks as a tool for utilizing laboratory information: Comparison with linear discriminant analysis and with classification and regression trees, Proc. Natl. Acad. Sci. USA., 88:11426-11430 (1991).
    • (1991) Proc. Natl. Acad. Sci. USA. , vol.88 , pp. 11426-11430
    • Reibnegger, G.1    Weiss, G.2    Werner-Felmayer, G.3    Judmaier, G.4    Wachter, H.5
  • 24
    • 0026075594 scopus 로고
    • Application of neural networks in quantitative structure-activity relationships of dihydrofolate reductase inhibitors
    • T. A. Andrea and H. Kalayeh, Application of neural networks in quantitative structure-activity relationships of dihydrofolate reductase inhibitors, J. Med. Chem., 34:2824-2836 (1991).
    • (1991) J. Med. Chem. , vol.34 , pp. 2824-2836
    • Andrea, T.A.1    Kalayeh, H.2
  • 27
    • 0027212862 scopus 로고
    • Statistics using neural networks: Chance effects
    • D. J. Livingstone and D. T. Manallack, Statistics using neural networks: Chance effects, J. Med. Chem., 36(9): 1295-1297 (1993).
    • (1993) J. Med. Chem. , vol.36 , Issue.9 , pp. 1295-1297
    • Livingstone, D.J.1    Manallack, D.T.2
  • 28
    • 0030048766 scopus 로고    scopus 로고
    • Statistical approach to neural network model building for gentamicin peak predictions
    • B. P Smith and M. E. Brier, Statistical approach to neural network model building for gentamicin peak predictions, J. Pharm. Sci., 85(1):65-69 (1996).
    • (1996) J. Pharm. Sci. , vol.85 , Issue.1 , pp. 65-69
    • Smith, B.P.1    Brier, M.E.2
  • 29
    • 0003271452 scopus 로고
    • Stopped training and other remedies for overfitting
    • SAS Institute Inc., Cary, NC
    • W. S. Sarle, Stopped training and other remedies for overfitting, Proceedings of the 27th Symposium on the Interface 1995, SAS Institute Inc., Cary, NC, (1995). ftp://ftp.sas.com/pub/sugi19/neural/interface95.ps
    • (1995) Proceedings of the 27th Symposium on the Interface 1995
    • Sarle, W.S.1
  • 31
    • 0020464111 scopus 로고
    • A simplified neuron modelled as a principal component analyzer
    • E. Oja, A simplified neuron modelled as a principal component analyzer, J. Math Biol., 15:267-273 (1982).
    • (1982) J. Math Biol. , vol.15 , pp. 267-273
    • Oja, E.1
  • 32
    • 0024883243 scopus 로고
    • Optimal unsupervised learning in a single layer linear feedforward network
    • T. Sanger, Optimal unsupervised learning in a single layer linear feedforward network, Neural Networks, 12:459-473 (1989).
    • (1989) Neural Networks , vol.12 , pp. 459-473
    • Sanger, T.1
  • 33
    • 0025489075 scopus 로고
    • The self-organizing map
    • T. Kohonen, The self-organizing map, Proc. IEEE, 78: 1464-1480 (1990).
    • (1990) Proc. IEEE , vol.78 , pp. 1464-1480
    • Kohonen, T.1
  • 34
    • 5244352553 scopus 로고
    • Competitive learning: From interactive activation to adaptive resonance
    • S. Grossberg, Competitive learning: From interactive activation to adaptive resonance, Cogn. Sci., 11:23-63 (1987).
    • (1987) Cogn. Sci. , vol.11 , pp. 23-63
    • Grossberg, S.1
  • 35
    • 85038604454 scopus 로고    scopus 로고
    • http://wwwipd.ira.uka.de/~prechelt/FAQ/neural-net-faq.html


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.