A Proposed Pathogen Classification System
Document Type Conference Paper
Artificial Intelligence & Cognitive Sciences Conference, Dublin 2012.
Abstract
Approximately 51% of patients that require treatment within hospital Intensive Care Units (ICU) acquire an infection [1]. Rapid identification of the pathogen and medical treatment has a significant impact on survival rates and reduces the associated treatment costs in hospitals and in the community. Bacterial identification with Vibrational Spectroscopy (VS by either Raman and Fourier Transform Infra-Red (FTIR) spectroscopy) has recently been proven to rapidly type bacterial strains using appropriate classification algorithms [2]. This poster details the challenges of classifying common pathogens using VS and machine learning methods to build a pathogen multi-classification system that would aim to deliver very high clinical classification accuracy.