Literature DB >> 18187228

Classifying algorithms for SIFT-MS technology and medical diagnosis.

K T Moorhead1, D Lee, J G Chase, A R Moot, K M Ledingham, J Scotter, R A Allardyce, S T Senthilmohan, Z Endre.   

Abstract

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.

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Year:  2008        PMID: 18187228     DOI: 10.1016/j.cmpb.2007.11.011

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  3 in total

1.  Optical Detection of Acetone Using "Turn-Off" Fluorescent Rice Straw Based Cellulose Carbon Dots Imprinted onto Paper Dipstick for Diabetes Monitoring.

Authors:  Mubark Alshareef; Razan M Snari; Omaymah Alaysuy; Afrah M Aldawsari; Hana M Abumelha; Hanadi Katouah; Nashwa M El-Metwaly
Journal:  ACS Omega       Date:  2022-05-05

2.  Highly Sensitive and Selective Gas Sensors Based on NiO/MnO2 @NiO Nanosheets to Detect Allyl Mercaptan Gas Released by Humans under Psychological Stress.

Authors:  Chunyan Li; Pil Gyu Choi; Yoshitake Masuda
Journal:  Adv Sci (Weinh)       Date:  2022-07-15       Impact factor: 17.521

3.  A sub-ppm acetone gas sensor for diabetes detection using 10 nm thick ultrathin InN FETs.

Authors:  Kun-Wei Kao; Ming-Che Hsu; Yuh-Hwa Chang; Shangjr Gwo; J Andrew Yeh
Journal:  Sensors (Basel)       Date:  2012-05-29       Impact factor: 3.576

  3 in total

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