@inproceedings{fbd896652b37478b913e04301ee0b35d,
title = "Exploring Memristive Biosensing Dynamics: A COMSOL Multiphysics Approach",
abstract = "This paper presents a novel methodology for mod-eling memristive biosensing within COMSOL Multiphysics, fo-cusing on critical performance metrics such as antigen-antibody binding concentration and output resistive states. By studying the impact of increasing inlet concentrations, insights into binding concentration curve and output resistance variations are uncov-ered. The resultant simulation data effectively trains a support vector machine classifier (SVMC), achieving a remarkable accu-racy rate of 97\%. The incorporation of artificial intelligence (AI) through SVM demonstrates promising strides in advancing AI-based memristive biosensing modeling, potentially elevating their performance standards and applicability across diverse domains.",
keywords = "antibody, antigen, biosensor, COMSOL, Memristor, modelling, resistance, SVM",
author = "Manel Bouzouita and Fakhreddine Zayer and Ioulia Tzouvadaki and Sandro Carrara and Hamdi Belgacem",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE BioSensors Conference, BioSensors 2024 ; Conference date: 28-07-2024 Through 30-07-2024",
year = "2024",
doi = "10.1109/BioSensors61405.2024.10712722",
language = "British English",
series = "2024 IEEE BioSensors Conference, BioSensors 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2024 IEEE BioSensors Conference, BioSensors 2024",
address = "United States",
}