RESUMEN
The Covid-19 pandemic is the defining global health crisis of our time. Chest X-Rays (CXR) have been an important imaging modality for assisting in the diagnosis and management of hospitalised Covid-19 patients. However, their interpretation is time intensive for radiologists. Accurate computer aided systems can facilitate early diagnosis of Covid-19 and effective triaging. In this paper, we propose a fuzzy logic based deep learning (DL) approach to differentiate between CXR images of patients with Covid-19 pneumonia and with interstitial pneumonias not related to Covid-19. The developed model here, referred to as CovNNet, is used to extract some relevant features from CXR images, combined with fuzzy images generated by a fuzzy edge detection algorithm. Experimental results show that using a combination of CXR and fuzzy features, within a deep learning approach by developing a deep network inputed to a Multilayer Perceptron (MLP), results in a higher classification performance (accuracy rate up to 81%), compared to benchmark deep learning approaches. The approach has been validated through additional datasets which are continously generated due to the spread of the virus and would help triage patients in acute settings. A permutation analysis is carried out, and a simple occlusion methodology for explaining decisions is also proposed. The proposed pipeline can be easily embedded into present clinical decision support systems.
Asunto(s)
Prueba de Ácido Nucleico para COVID-19/instrumentación , COVID-19/diagnóstico , Técnicas de Amplificación de Ácido Nucleico/instrumentación , SARS-CoV-2/aislamiento & purificación , COVID-19/virología , Diseño de Equipo , Humanos , Pruebas en el Punto de Atención , ARN Viral/análisis , ARN Viral/genética , SARS-CoV-2/genéticaRESUMEN
PCR has become one of the most valuable techniques currently used in bioscience, diagnostics and forensic science. Here we review the history of PCR development and the technologies that have evolved from the original PCR method. Currently, there are two main areas of PCR utilization in bioscience: high-throughput PCR systems and microfluidics-based PCR devices for point-of-care (POC) applications. We also discuss the commercialization of these techniques and conclude with a look into their modifications and use in innovative areas of biomedicine. For example, real-time reverse transcription PCR is the gold standard for SARS-CoV-2 diagnoses. It could also be used for POC applications, being a key component of the sample-to-answer system.