An Automatic Analysis Platform for Rapid Antibiotics Susceptibility Prediction to Bacteria Based on Mass Spectra Data Using a Machine Learning Approach(3/3)

Project Details

Description

Antibiotics susceptibility test (AST) is an in-vitro test for providing information of microorganism against antibiotics. The test result could be susceptible or resistant, which guides clinical physicians for correct use of antibiotics. The current AST procedure in clinical microbiology laboratory would spend several days, which hinder correct and timely treatment against infectious disease. In contrast, rapid AST aims to provide accurate AST in shorter turn-around-time, which could reduce mortality, avoid drug resistance, and shorten length of stay in hospital. In recent years, matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) has become an alternative and powerful tool in clinical microbiology laboratories for rapid bacteria species identification. However, rapid AST still cannot be obtained from the MALDI-TOF MS spectra. Therefore, the primary objective of this project is to construct a large database system composed of MALDI-TOF MS data and AST obtained from Chang Gung Memorial Hospitals (Linkou and Kaohsiung branches). On the basis of the database, prediction models capable of providing rapid AST will be developed, validated, and tested by an independent dataset. Moreover, informative features will be selected by feature selection methods to provide clues for further development of new drugs. Finally, a web-based tool for rapid AST will be developed to apply in the clinical medicine.
StatusActive
Effective start/end date1/08/2131/07/22

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 8 - Decent Work and Economic Growth
  • SDG 17 - Partnerships for the Goals

Keywords

  • antibiotics susceptibility test
  • matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS)
  • machine learning
  • multidrug resistance

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