An Artificial Intelligence-Assisted Portable Low-Cost Devicefor the Rapid Detection of SARS-CoV-2. - Tharmakulasingam, M.; Chaudhry, N.S.; Branavan, M.; Balachandran, W.; Poirier, A.C.; Rohaim, M.A.; Munir, M.; Ragione, R.M.L.; Fernando, A. (MDPI, 2021)
An artificial intelligence-assisted low-cost portable device for the rapid detection of se-vere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is presented here. This standalonetemperature-controlled device houses tubes designed for conducting reverse transcription loop-mediated isothermal amplification (RT-LAMP) assays. Moreover, the device utilises tubes illuminatedby LEDs, an in-built camera, and a small onboard computer with automated image acquisition andprocessing algorithms. This intelligent device significantly reduces the normal assay run time andremoves the subjectivity associated with operator interpretation of colourimetric RT-LAMP results.To further improve this device’s usability, a mobile app has been integrated into the system to controlthe LAMP assay environment and to visually display the assay results by connecting the device toa smartphone via Bluetooth. This study was undertaken using ~5000 images produced from the~200 LAMP amplification assays using the prototype device. Synthetic RNA and a small panel ofpositive and negative SARS-CoV-2 patient samples were assayed for this study. State-of-the-art imageprocessing and artificial intelligence algorithms were applied to these images to analyse them andto select the most efficient algorithm. The template matching algorithm for image extraction andMobileNet CNN architecture for classification results provided 98.0% accuracy with an average runtime of 20 min to confirm the endpoint result. Two working points were chosen based on the bestcompromise between sensitivity and specificity. The high sensitivity point has a sensitivity value of99.12% and specificity value of 70.8%, while at the high specificity point, the sensitivity is 96.05%and specificity 93.59%. Furthermore, this device provides an efficient and cost-effective platform fornon-health professionals to detect not only SARS-CoV-2 but also other pathogens in resource-limitedlaboratories, factories, airports, schools, universities, and homes.
Keywords: Artificial intelligence; SARS-CoV-2; Rapid detection; Portable device; Image processing; LAMP