Mass spectral search method using the Neural Network approach

Chong Sze Tong*, K. C. Cheng

*Corresponding author for this work

Research output: Contribution to conferenceConference paperpeer-review


This paper investigates the use of Neural Networks as a novel approach in the implementation of spectral library search for gas chromatography mass spectrometry. A total of 28 drugs currently under control in Hong Kong were chosen for the study. Real forensic data, which represents mass spectra obtained under various conditions ranging from good to poor, were used for mining and testing. A total of 355 spectra were used for training the neural networks, and a further set of 163 spectra was used for evaluation. All the neural networks considered performed better than the conventional benchmark, with recognition rates above 97.5%.

Original languageEnglish
Number of pages6
Publication statusPublished - 1999
EventInternational Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
Duration: 10 Jul 199916 Jul 1999


ConferenceInternational Joint Conference on Neural Networks (IJCNN'99)
CityWashington, DC, USA

Scopus Subject Areas

  • Software
  • Artificial Intelligence


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