Deep Optical Blood Analysis: Covid-19 Detection As A Case Study In Next Generation Blood Screening

A wide variety of diseases are commonly diagnosed via the visual examination of cell morphology within a peripheral blood smear. For certain diseases, such as COVID-19, morphological impact across the multitude of blood cell types is still poorly understood. In this paper, we present a multiple instance learning-based approach to aggregate high-resolution morphological information across many blood cells and cell types to automatically diagnose disease at a per-patient level. We integrated image and diagnostic information from across 236 patients to demonstrate not only that there is a significant link between blood and a patient’s COVID-19 infection status, but also that novel machine learning approaches offer a powerful and scalable means to analyze peripheral blood smears. Our results both backup and enhance hematological findings relating blood cell morphology to COVID-19, and offer a high diagnostic efficacy; with a 79% accuracy and a ROC-AUC of 0.90. ### Competing Interest Statement Carolyn Glass is a voluntary advisor to SafineAI, a firm designing optical imaging solutions for peripheral blood smears. Chad McCall is the Secretary Treasurer of the North Carolina Society of Pathologists. Roarke Horstmeyer is a scientific advisor for SafineAI (mentioned above), as well as Ramona Optics, a firm designing optical microscopes. ### Funding Statement This study was funded by Duke University, the Duke-Coulter Translational Partnership, and the Natural Sciences and Engineering Research Council (NSERC) of Canada (fellowship of Colin Cooke). ### 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: The Duke University Health System Institutional Review Board (DUHS IRB) has determined that the following protocol meets the criteria for a declaration of exemption from further IRB review as described in 45 CFR 46.101(b), 45 CFR 46.102 (f), or 45 CFR 46.102 (d), satisfies the Privacy Rule as described in 45 CFR 164.512(i), and satisfies Food and Drug Administration regulations as described in 21 CFR 56.104, where applicable. Duke University Health System Institutional Review Board 2424 Erwin Rd | Suite 405 | Durham, NC | 919.668.5111 Federalwide Assurance No: FWA 00009025 All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. 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 is not made available at this point.