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Background: As the COVID-19 pandemic continues to spread worldwide, there is still no accurate rapid diagnostic test for COVID-19, or monitoring tool for patient’s clinical course. An artificial-intelligence system (CoviDet) was therefore developed and applied on chest computed tomography (CT), to evaluate its application for rapid diagnosis and potential monitoring of COVID-19 patients. Methods: 1,201,074 CT slices from 2527 patients were grouped into 3 main groups: COVID-19 positive group, non-COVID-19 viral pneumonia group and control group. They were used to train and validate CoviDet novel stepwise diagnostic algorithm to diagnose COVID-19, with or without clinical data. A subset of COVID-19 patients with more than 3 consecutive CT images were selected for training and validation of the auto-segmentation and monitoring algorithm. Findings: CoviDet outperforms radiologists, and can diagnose COVID-19 based on CT alone with sensitivity of 0.93, specificity of 0.95 and AUC of 0.98 (95%CI 0.97-0.99; P

Recently, it has been reported that the microRNA-132(miR-132) is linked with synaptic plasticity and cognitive impairment. The present study investigates that whether miR-132 is altered in circulating blood serum samples of post-stroke cognitive impairment (PSCI) patients.We collected samples from 39 subjects with PSCI, 37 subjects with post-stroke cognitive normality (PSCN), and 38 age-matched controls (AMC) for which ages, gender and education level were matched. MiR-132 was detected using a quantitative real-time PCR (qRT-PCR) method. To test the predictive value of miR-132 for PSCI, prediction capabilities were compared using the receiver operating characteristic (ROC) curves and area under curve (AUC) analysis.The level of miR-132 in PSCI patient serum was significantly elevated compared to that of PSCN and AMC subjects. The ROC curve showed that miR-132 achieved an AUC of 0.961 (p0.0001). Importantly, the miR-132 level was correlated with the Montreal Cognitive Assessment (MoCA) score in PSCI patients.These results indicated that there was a substantial correlation between serum miR-132 expression and post-stroke cognitive functionality, suggesting that miR-132 may be a risk marker for PSCI. Because of the limitations of this study, the results should be treated with caution.