Classifying algorithms for SIFT-MS technology and medical diagnosis
Copyright policy )Classifying algorithms for SIFT-MS technology and medical diagnosis
Selected Ion Flow Tube-Mass Spectrometry (SIFT-MS) is an analytical technique for real-time quantification of trace gases in air or breath samples. SIFT-MS system thus offers unique potential for early, rapid detection of disease states. Identification of volatile organic compound (VOC) masses that contribute strongly towards a successful classification clearly highlights potential new biomarkers. A method utilising kernel density estimates is thus presented for classifying unknown samples. It is validated in a simple known case and a clinical setting before-after dialysis. The simple case with nitrogen in Tedlar bags returned a 100% success rate, as expected. The clinical proof-of-concept with seven tests on one patient had an ROC curve area of 0.89. These results validate the method presented and illustrate the emerging clinical potential of this technology.
- University of Otago New Zealand
- University of Canterbury New Zealand
Fields of Research::250000 Chemical Sciences::250400 Analytical Chemistry::250402 Analytical spectrometry, Spectrometry, Mass, Electrospray Ionization, Nitrogen, kernel classifier, SIFT-MS, Kidney, Pattern Recognition, Automated, Artificial Intelligence, Renal Dialysis, diagnostics, Humans, Computer Simulation, Diagnosis, Computer-Assisted, breath analysis, Organic Chemicals, Fields of Research::280000 Information, VOC, Reproducibility of Results, classification, Breath Tests, Computing and Communication Sciences::280400 Computation Theory and Mathematics, Kidney Diseases, Gases, Volatilization, Algorithms, Biomarkers
Fields of Research::250000 Chemical Sciences::250400 Analytical Chemistry::250402 Analytical spectrometry, Spectrometry, Mass, Electrospray Ionization, Nitrogen, kernel classifier, SIFT-MS, Kidney, Pattern Recognition, Automated, Artificial Intelligence, Renal Dialysis, diagnostics, Humans, Computer Simulation, Diagnosis, Computer-Assisted, breath analysis, Organic Chemicals, Fields of Research::280000 Information, VOC, Reproducibility of Results, classification, Breath Tests, Computing and Communication Sciences::280400 Computation Theory and Mathematics, Kidney Diseases, Gases, Volatilization, Algorithms, Biomarkers
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).21 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
Citations provided by BIP!Popularity provided by BIP!