Calibration and Inter-Unit Consistency Assessment of an Electrochemical Sensor System Using Machine Learning

Research output: Contribution to a Journal (Peer & Non Peer) › Article › peer-review

18 Citations (Scopus)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

@article{254b5731873f405c869135335e88732d,

title = "Calibration and Inter-Unit Consistency Assessment of an Electrochemical Sensor System Using Machine Learning",

author = "Apostolopoulos, \{Ioannis D.\} and Silas Androulakis and Panayiotis Kalkavouras and George Fouskas and Pandis, \{Spyros N.\}",

year = "2024",

month = jun,

doi = "10.3390/s24134110",

language = "Undefined/Unknown",

journal = "Sensors",

publisher = "MDPI",

}

TY - JOUR

T1 - Calibration and Inter-Unit Consistency Assessment of an Electrochemical Sensor System Using Machine Learning

AU - Apostolopoulos, Ioannis D.

AU - Androulakis, Silas

AU - Kalkavouras, Panayiotis

AU - Fouskas, George

AU - Pandis, Spyros N.

PY - 2024/6

Y1 - 2024/6

UR - https://www.mdpi.com/1424-8220/24/13/4110

U2 - 10.3390/s24134110

DO - 10.3390/s24134110

M3 - Article

JO - Sensors

JF - Sensors

ER -