Performance of an artificial intelligence-based smartphone app for guided reading of SARS-CoV-2 lateral-flow immunoassays

Objectives To evaluate an artificial intelligence-based smartphone application to automatically and objectively read rapid diagnostic test (RDT) results and assess its impact on COVID-19 pandemic management. Methods Overall, 252 human sera from individuals with PCR-positive SARS-CoV-2 infection were used to inoculate a total of 1165 RDTs for training and validation purposes. We then conducted two field studies to assess the performance on real-world scenarios by testing 172 antibody RDTs at two nursing homes and 92 antigen RDTs at one hospital emergency department. Results Field studies demonstrated high levels of sensitivity (100%) and specificity (94.4%, CI 92.8-96.1%) for reading IgG band of COVID-19 antibodies RDTs compared to visual readings from health workers. Sensitivity of detecting IgM test bands was 100% and specificity was 95.8%, CI 94.3-97.3%. All COVID-19 antigen RDTs were correctly read by the app. Conclusions The proposed reading system is automatic, reducing variability and uncertainty associated with RDTs interpretation and can be used to read different RDTs brands. The platform can serve as a real time epidemiological tracking tool and facilitate reporting of positive RDTs to relevant health authorities. ### Competing Interest Statement DBP, EA, AM, ED, LL, AV, DC and MLO work for Spotlab. ### Funding Statement This study was partially funded by Jylag Foundation. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics approval for the study was obtained from the Clinical Research Ethics Committee of the Ramon y Cajal University Hospital (Ref. 127/21). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Data produced in the present study will be available upon reasonable request to the authors