Data-Driven Modeling of Smartphone-Based Electrochemiluminescence Sensor Data Using Artificial Intelligence

Understanding relationships among multimodal data extracted from a smartphone-based electrochemiluminescence (ECL) sensor is crucial for the development of low-cost point-of-care diagnostic devices. In this work, artificial intelligence (AI) algorithms such as random forest (RF) and feedforward neur...

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Detalles Bibliográficos
Autores principales: Ccopa Rivera, Elmer, Swerdlow, Jonathan J., Summerscales, Rodney L., Uppala, Padma P. Tadi, Maciel Filho, Rubens, Neto, Mabio R. C., Kwon, Hyun J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038330/
https://www.ncbi.nlm.nih.gov/pubmed/31979213
http://dx.doi.org/10.3390/s20030625

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038330/
https://www.ncbi.nlm.nih.gov/pubmed/31979213
http://dx.doi.org/10.3390/s20030625

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