- Joined
- Feb 20, 2012
- Messages
- 401
BBC news report: http://www.bbc.co.uk/news/health-26769388
Scientific paper: http://iopscience.iop.org/1752-7163/8/2/026001/article
The use of a gas chromatograph coupled to a metal oxide sensor for rapid assessment of stool samples from irritable bowel syndrome and inflammatory bowel disease patients
Abstract
There is much clinical interest in the development of a low-cost and reliable test for diagnosing inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS), two very distinct diseases that can present with similar symptoms. The assessment of stool samples for the diagnosis of gastro-intestinal diseases is in principle an ideal non-invasive testing method. This paper presents an approach to stool analysis using headspace gas chromatography and a single metal oxide sensor coupled to artificial neural network software. Currently, the system is able to distinguish samples from patients with IBS from patients with IBD with a sensitivity and specificity of 76% and 88% respectively, with an overall mean predictive accuracy of 76%.
Scientific paper: http://iopscience.iop.org/1752-7163/8/2/026001/article
The use of a gas chromatograph coupled to a metal oxide sensor for rapid assessment of stool samples from irritable bowel syndrome and inflammatory bowel disease patients
Abstract
There is much clinical interest in the development of a low-cost and reliable test for diagnosing inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS), two very distinct diseases that can present with similar symptoms. The assessment of stool samples for the diagnosis of gastro-intestinal diseases is in principle an ideal non-invasive testing method. This paper presents an approach to stool analysis using headspace gas chromatography and a single metal oxide sensor coupled to artificial neural network software. Currently, the system is able to distinguish samples from patients with IBS from patients with IBD with a sensitivity and specificity of 76% and 88% respectively, with an overall mean predictive accuracy of 76%.