Go Green! Reusing Brain Monitoring Data Containing Missing Values: A Feasibility Study with Traumatic Brain Injury Patients

Autor:	Kuralmani Vellaisamy, Pei Loon Chin, Liang Yu Loy, Liang Shen, Kah Keow Lee, Mengling Feng, Beng Ti Ang, Zhuo Zhang, Nicolas Kon Kam King, Cuntai Guan, Feng Zhang
Rok vydání:	2012
Předmět:	Traumatic brain injury Brain monitoring Reuse computer.software_genre medicine.disease Missing data Statistical power Support vector machine Monitoring data medicine Data mining Imputation (statistics) Medical emergency Psychology computer
Zdroj:	Acta Neurochirurgica Supplementum ISBN: 9783709109557
DOI:	10.1007/978-3-7091-0956-4_10
Popis:	Background: Despite the wealth of information carried, periodic brain monitoring data are often incomplete with a significant amount of missing values. Incomplete monitoring data are usually discarded to ensure purity of data. However, this approach leads to the loss of statistical power, potentially biased study and a great waste of resources. Thus, we propose to reuse incomplete brain monitoring data by imputing the missing values – a green solution! To support our proposal, we have conducted a feasibility study to investigate the reusability of incomplete brain monitoring data based on the estimated imputation error.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a4182290a3a3d1dd728e292c534409b2 https://doi.org/10.1007/978-3-7091-0956-4_10 Zobrazit plný text záznamu