Testing of a Short-Term Blood Glucose Prediction Algorithm Using the DirecNet Database

Autor:	K. V. Pozhar, V. M. Grinval’d, P. A. Rudenko, N. A. Bazaev, Evgeniia L. Litinskaia
Rok vydání:	2019
Předmět:	Database Computer science Mean squared prediction error 0206 medical engineering Biomedical Engineering Stability (learning theory) Medicine (miscellaneous) 02 engineering and technology computer.software_genre 020601 biomedical engineering Term (time) Medical Laboratory Technology Noise Algorithm computer
Zdroj:	Biomedical Engineering. 52:419-422
ISSN:	1573-8256 0006-3398
DOI:	10.1007/s10527-019-09860-w
Popis:	A short-term blood glucose prediction algorithm was validated using the DirecNet clinical database. Noise at 0, 10, 15, 20, and 25% levels was added to blood glucose tracks to assess the stability of the algorithm. Computer modeling showed that the average prediction error was 2.0, 3.0, 6.6, 7.4, and 13.7%, respectively.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1d7580705772190ee9ffe3cb32a505a9 https://doi.org/10.1007/s10527-019-09860-w Zobrazit plný text záznamu Full text from SpringerLink