Enhancement of precision in the analysis of medicines by
capillary electrophoresis using artificial neural networks

J 2002

Enhancement of precision in the analysis of medicines by capillary electrophoresis using artificial neural networks

LI, Hua, YX ZHANG, Pavla POLÁŠKOVÁ and Josef HAVEL

Basic information

Original name

Enhancement of precision in the analysis of medicines by capillary electrophoresis using artificial neural networks

Authors

LI, Hua (156 China), YX ZHANG (156 China), Pavla POLÁŠKOVÁ (203 Czech Republic) and Josef HAVEL (203 Czech Republic, guarantor)

Edition

ACTA CHIMICA SINICA, BEIJING, SCIENCE CHINA PRESS, 2002, 0567-7351

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10406 Analytical chemistry

Country of publisher

China

Confidentiality degree

není předmětem státního či obchodního tajemství

Impact factor

Impact factor: 0.536

RIV identification code

RIV/00216224:14310/02:00007967

Organization unit

Faculty of Science

UT WoS

000176934200022

Keywords in English

Enhancement of precision; analysis of medicines; capillary electrophoresis

Abstract

V originále

Possibility of increasing the precision of quantitative determination of memantine by capillary electrophoresis (CE) was studied using artificial neural networks (ANNs). ANNs show their unique merits in the calibration of non-linear models. In the analysis of memantine by CE, there is no obvious linear relationships between the concentrations of the memantine and its peak areas or heights, or even their ratios to those of the corresponding internal standards, respectively. The greatest advantage of ANNs is that no prior knowledge of migration behavior and separation system is needed. The inputs of the ANNs were the peak areas and heights of memantine, and the outputs were the concentrations of the memantine. The 2:2: 1 ANNs gave excellent results. The ANNs approach can also he used to improve the precision of determination of other kinds of analytes for its general validity.

Links

GA203/02/1103, research and development project

Name: Umělé neuronové sítě a plánování pokusů v analytické chemii, zejména v separačních metodách

Investor: Czech Science Foundation, Artificial neural networks and experimental design in analytical chemistry, especially in separation methods

Citovat

LI, Hua, YX ZHANG, Pavla POLÁŠKOVÁ and Josef HAVEL. Enhancement of precision in the analysis of medicines by capillary electrophoresis using artificial neural networks. ACTA CHIMICA SINICA. BEIJING: SCIENCE CHINA PRESS, 2002, vol. 60, No 7, p. 1264-1268. ISSN 0567-7351.

@article{485223,
   author = {Li, Hua and Zhang, YX and Polášková, Pavla and Havel, Josef},
   article_location = {BEIJING},
   article_number = {7},
   keywords = {Enhancement of precision; analysis of medicines; capillary electrophoresis},
   language = {eng},
   issn = {0567-7351},
   journal = {ACTA CHIMICA SINICA},
   title = {Enhancement of precision in the analysis of medicines by capillary electrophoresis using artificial neural networks},
   volume = {60},
   year = {2002}
}

TY  - JOUR
ID  - 485223
AU  - Li, Hua - Zhang, YX - Polášková, Pavla - Havel, Josef
PY  - 2002
TI  - Enhancement of precision in the analysis of medicines by capillary electrophoresis using artificial neural networks
JF  - ACTA CHIMICA SINICA
VL  - 60
IS  - 7
SP  - 1264-1268
EP  - 1264-1268
PB  - SCIENCE CHINA PRESS
SN  - 05677351
KW  - Enhancement of precision
KW  - analysis of medicines
KW  - capillary electrophoresis
N2  - Possibility of increasing the precision of quantitative determination of memantine by capillary electrophoresis (CE) was studied using artificial neural networks (ANNs). ANNs show their unique merits in the calibration of non-linear models. In the analysis of memantine by CE, there is no obvious linear relationships between the concentrations of the memantine and its peak areas or heights, or even their ratios to those of the corresponding internal standards, respectively. The greatest advantage of ANNs is that no prior knowledge of migration behavior and separation system is needed. The inputs of the ANNs were the peak areas and heights of memantine, and the outputs were the concentrations of the memantine. The 2:2: 1 ANNs gave excellent results. The ANNs approach can also he used to improve the precision of determination of other kinds of analytes for its general validity.
ER  -

LI, Hua, YX ZHANG, Pavla POLÁŠKOVÁ and Josef HAVEL. Enhancement of precision in the analysis of medicines by capillary electrophoresis using artificial neural networks. \textit{ACTA CHIMICA SINICA}. BEIJING: SCIENCE CHINA PRESS, 2002, vol.~60, No~7, p.~1264-1268. ISSN~0567-7351.

Detailed Information on Publication Record