<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>In this paper we introduce two confidence and two prediction regions for statistical characterization of concentration measurements of product ions in order to discriminate various groups of persons for prospective better detection of primary lung cancer. Two MATLAB algorithms have been created for more adequate description of concentration measurements of volatile organic compounds in human breath gas for potential detection of primary lung cancer and for evaluation of the appropriate confidence and prediction regions.</p></abstract>

In this paper we introduce two confidence and two prediction regions for statistical characterization of concentration measurements of product ions in order to discriminate various groups of persons for prospective better detection of primary lung cancer. Two MATLAB algorithms have been created for more adequate description of concentration measurements of volatile organic compounds in human breath gas for potential detection of primary lung cancer and for evaluation of the appropriate confidence and prediction regions.

Statistical Method Based on Confidence and Prediction Regions for Analysis of Volatile Organic Compounds in Human Breath Gas

Institute of Measurement Science, Slovak Academy of Sciences, Dúbravská cesta 9, 84104 Bratislava, Slovakia Mathematical Institute, Slovak Academy of Sciences Štefánikova 49, 814 73 Bratislava

Measurement Science Review

In this paper we introduce two confidence and two prediction regions for statistical characterization of concentration measurements of product ions in order to...

Statistical Method Based on Confidence and Prediction Regions for Analysis of Volatile Organic Compounds in Human Breath Gas

Data publikacji: 24 paź 2008

Zakres stron: 111 - 113

DOI: https://doi.org/10.2478/v10048-008-0026-7

Słowa kluczowe
breath gas concentration, lung cancer detection, linear regression model, confidence interval, prediction interval

This content is open access.

Statistical Method Based on Confidence and Prediction Regions for Analysis of Volatile Organic Compounds in Human Breath Gas

Data publikacji: 24 paź 2008

Zakres stron: 111 - 113

DOI: https://doi.org/10.2478/v10048-008-0026-7

Słowa kluczowebreath gas concentration, lung cancer detection, linear regression model, confidence interval, prediction interval

This content is open access.

Słowa kluczowe
breath gas concentration, lung cancer detection, linear regression model, confidence interval, prediction interval