Detection of COVID-19: A Smartphone-Based Machine-Learning-Assisted ECL Immunoassay Approach with the Ability of RT-PCR CT Value Prediction-Reference-Cited by-同舟云学术

Detection of COVID-19: A Smartphone-Based Machine-Learning-Assisted ECL Immunoassay Approach with the Ability of RT-PCR CT Value Prediction

Published:2022-11-16 Issue:47 Volume:94 Page:16361-16368
ISSN:0003-2700
Container-title:Analytical Chemistry
language:en
Short-container-title:Anal. Chem.

Author:

Firoozbakhtian Ali¹^ORCID,Hosseini Morteza¹²^ORCID,Sheikholeslami Mahsa Naghavi³,Salehnia Foad⁴,Xu Guobao⁵⁶^ORCID,Rabbani Hodjattallah⁷,Sobhanie Ebtesam¹

Affiliation:

1. Nanobiosensors Lab, Department of Life Science Engineering, Faculty of New Sciences & Technologies, University of Tehran, Tehran1439817435, Iran

2. National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran1439817435, Iran

3. Center of Excellence in Electrochemistry, School of Chemistry, College of Science, University of Tehran, Tehran1439817435, Iran

4. Departament d’Enginyeria Electrònica, Escola Tècnica Superior d’Enginyeria, Universitat Rovira i Virgili, Avinguda dels Països Catalans 26, 43007Tarragona, Spain

5. State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun130022, China

6. University of Science and Technology of China, Hefei, Anhui230026, China

7. Monoclonal Antibody Research Center, Avicenna Research Institute, ACECR, Tehran1439817435, Iran

Funder

Iran National Science Foundation

University of Tehran

Agence Universitaire de la Francophonie

Chinese Academy of Sciences

Publisher

American Chemical Society (ACS)

Subject

Analytical Chemistry