TY  - CONF
AU  - Ispizua, Begoña
AU  - Manjarrés, Diana
AU  - Niño-Adan, Iratxe
A4  - Jiang, Xingpeng
A4  - Wang, Haiying
A4  - Alhajj, Reda
A4  - Hu, Xiaohua
A4  - Engel, Felix
A4  - Mahmud, Mufti
A4  - Pisanti, Nadia
A4  - Cui, Xuefeng
A4  - Song, Hong
PY  - 2023
DO  - 10.1109/BIBM58861.2023.10385780
SN  - 9798350337488
UR  - https://hdl.handle.net/11556/5008
AB  - Metabolic syndrome (MetS) is considered to be a major public health problem worldwide leading to a high risk of diabetes and cardiovascular diseases. In this paper, data collected by the Precision Medicine Initiative of the Basque Country, named the...
LA  - eng
PB  - Institute of Electrical and Electronics Engineers Inc.
TI  - Prediction of Metabolic Syndrome Based on Machine Learning Techniques with Emphasis on Feature Relevances and Explainability Analysis
TY  - conference output
ER  -