Machine Learning and Data Mining Methods in Diabetes Research

The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, application of machine learning and data mining methods in bio...

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Vydané v:	Computational and structural biotechnology journal Ročník 15; s. 104 - 116
Hlavní autori:	Kavakiotis, Ioannis, Tsave, Olga, Salifoglou, Athanasios, Maglaveras, Nicos, Vlahavas, Ioannis, Chouvarda, Ioanna
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Netherlands Elsevier B.V 01.01.2017 Research Network of Computational and Structural Biotechnology Elsevier
Predmet:	Biomarker(s) identification biotechnology data collection Data mining Diabetes mellitus Diabetic complications Disease prediction models genetic background health services human health Machine learning prediction Review support vector machines systematic review therapeutics Diabetic complications Data mining Disease prediction models Diabetes mellitus Machine learning Biomarker(s) identification
ISSN:	2001-0370, 2001-0370
On-line prístup:	Získať plný text
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