Open AccessCompendium of Tunable Data-driven Approaches for Smoothing Parameter Learning for Kernel Density-based Normal Systolic Blood Pressure Detection
Author(s) -
David Kwamena Mensah,
Francis Eyiah-Bediako,
Samuel Assabil
Publication year - 2022
Publication title -
universal journal of public health
Language(s) - English
Resource type - Journals
eISSN - 2331-8945
pISSN - 2331-8880
DOI - 10.13189/ujph.2022.100209
Subject(s) - compendium , smoothing , blood pressure , kernel (algebra) , computer science , cardiology , medicine , artificial intelligence , mathematics , computer vision , geography , discrete mathematics , archaeology
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