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The work done in this paper tries to bridge the gap between machine learning applications and their computing infrastructure for COVID-19.Pandemic novel Coronavirus (Covid-19) is an infectious disease that primarily spreads by droplets of nose discharge when sneezing and saliva from the mouth when coughing, that had first been reported in Wuhan, China in December 2019. Covid-19 became a global pandemic, which led to a harmful impact on the world. Many predictive models of Covid-19 are being proposed by academic researchers around the world to take the foremost decisions and enforce the appropriate control measures. Due to the lack of accurate Covid-19 records and uncertainty, the standard techniques are being failed to correctly predict the epidemic global effects. To address this issue, we present an Artificial Intelligence (AI)-based meta-analysis to predict the trend of epidemic Covid-19 over the world. The powerful machine learning algorithms namely Naïve Bayes, Support Vector Machine (SVM) and Linear Regression were applied on real time-series dataset, which holds the global record of confirmed, recovered, deaths and active cases of Covid-19 outbreak. Statistical analysis has also been conducted to present various facts regarding Covid-19 observed symptoms, a list of Top-20 Coronavirus affected countries and a number of coactive cases over the world. Among the three machine learning techniques investigated, Naïve Bayes produced promising results to predict Covid-19 future trends with less Mean Absolute Error (MAE) and Mean Squared Error (MSE). The less value of MAE and MSE strongly represent the effectiveness of the Naïve Bayes regression technique. Although, the global footprint of this pandemic is still uncertain. This study demonstrates the various trends and future growth of the global pandemic for a proactive response from the citizens and governments of countries. This paper sets the initial benchmark to demonstrate the capability of machine learning for outbreak prediction.Covid-19 is an acute respiratory infection and presents various clinical features ranging from no symptoms to severe pneumonia and death. Medical expert systems, especially in diagnosis and monitoring stages, can give positive consequences in the struggle against Covid-19. In this study, a rule-based expert system is designed as a predictive tool in self-pre-diagnosis of Covid-19. The potential users are smartphone users, healthcare experts and government health authorities. The system does not only share the data gathered from the users with experts, but also analyzes the symptom data as a diagnostic assistant to predict possible Covid-19 risk. To do this, a user needs to fill out a patient examination card that conducts an online Covid-19 diagnostic test, to receive an unconfirmed online test prediction result and a set of precautionary and supportive action suggestions. The system was tested for 169 positive cases. The results produced by the system were compared with the real PCR test results for the same cases. For patients with certain symptomatic findings, there was no significant difference found between the results of the system and the confirmed test results with PCR test. Furthermore, a set of suitable suggestions produced by the system were compared with the written suggestions of a collaborated health expert. The suggestions deduced and the written suggestions of the health expert were similar and the system suggestions in line with suggestions of the expert. The system can be suitable for diagnosing and monitoring of positive cases in the areas other than clinics and hospitals during the Covid-19 pandemic. The results of the case studies are promising, and it demonstrates the applicability, effectiveness, and efficiency of the proposed approach in all communities.Countries opting to eliminate covid-19 rather than reduce its spread have fared best - and there's still time to adopt the strategy, reports Graham Lawton.

Due to their professional characteristics and future career orientation, medical students have a deeper understanding of COVID-19 and enact disease prevention and control measures, which may cause psychological burden. We aimed to assess the psychological impact during the COVID-19 outbreak period(OP) and remission period(RP) among medical students.

We surveyed the medical students in Shantou University Medical College twice-during the OP and the RP, surveying psychological burden of COVID-19 lockdowns and its associated factors. 1069 respondents were recruited in OP and 1511 participants were recruited in RP. We constructed nomograms to predict the risk of psychological burden using risk factors that were screened through univariate analysis of the surveyed data set.

There was a statistically significant longitudinalincrement in psychological burden from OP to RP, and stress as well as cognition in psychological distress were the most dominant ones. Common impact factors of the depression, anxiety and stress included frequency of outdoor activities, mask-wearing adherence, self-perceived unhealthy status and exposure to COVID-19. In addition, the high frequency of handwashing was a protective factor for depression and anxiety. The C-index was 0.67, 0.74 and 0.72 for depression, anxiety and stress, respectively.

The psychological impact of COVID-19 was worse during the RP than during the OP. Thus, it's necessary to continue to emphasize the importance of mental health in medical students during the pandemic and our proposed nomograms can be useful tools for screening high-riskgroups for psychological burden risk in medical students.

The psychological impact of COVID-19 was worse during the RP than during the OP. Thus, it's necessary to continue to emphasize the importance of mental health in medical students during the pandemic and our proposed nomograms can be useful tools for screening high-risk groups for psychological burden risk in medical students.The goals of this study were to examine the longitudinal relations between school readiness and reading and math achievement and to test if these relations were moderated by temperament. The sample included socio-economically and ethnically diverse twins (N=551). Parents reported on school readiness when children were five years old. Teachers reported on temperament (effortful control, anger, and shyness) three years later. Standardized measures of reading and math were obtained when children were eight years old. Effortful control and shyness moderated the effect of school readiness on reading. Prediction of reading from school readiness was strongest when students were high in effortful control and low in shyness. Effortful control and shyness predicted math beyond school readiness. There were no relations involving anger. Findings demonstrate that temperament can potentiate the relations between school readiness and reading and highlight the importance of promoting school readiness and effortful control, while decreasing shyness.Children with autism are at high risk for self-regulation difficulties because of language delays and emotion-regulation difficulties. In typically-developing children, language development helps promote self-regulation, and in turn, cognitive development. Little research has examined the association between self-regulation and cognitive-skill development in children with autism. Children with autism (5-8 years), who were minimally-verbal (n=38) or typically-verbal (n=46) participated in a structured cognitive assessment and were observed for self-regulation difficulties during the cognitive assessment at the beginning and end of an academic year. Results showed that children with autism who were minimally- compared to typically-verbal had more self-regulation difficulties. Increase in self-regulation difficulties predicted less cognitive-skill gains, regardless of verbal ability, and cognitive skill gains also predicted changes in self-regulation difficulties. Interventions targeting self-regulation may be appropriate for all children with autism and should be adapted for minimally-verbal children.The outbreak of COVID-19 could increase adolescents' psychological distress and have a detrimental effect on their mental health. However, the negative effect of the COVID-19 pandemic on adolescents' mental health might be moderated by their existing psychological resources. The present study sought to investigate whether the relationship between adolescents' perceived stress of the COVID-19 pandemic and their depression symptoms was alleviated by their character strengths. A total of 617 adolescents were recruited and completed the online survey during the COVID-19 pandemic. The results indicated that adolescents' perceived stress of the COVID-19 pandemic was significantly positively correlated with their depression symptoms. Character strengths were significantly negatively correlated with adolescents' perceived stress of the COVID-19 pandemic and their depression symptoms. Moreover, the moderating effect of character strengths on the relationship between adolescents' perceived stress of the COVID-19 pandemic and their depression symptoms was significant. Therefore, adolescents' character strengths as a protective factor could buffer the effect of perceived stress of the COVID-19 pandemic on their depression symptoms and contribute to maintaining their mental health.The coronavirus (COVID-19) pandemic has impacted young adults across a number of different domains. It is critical to establish the degree to which the COVID-19 pandemic has affected mental health and identify predictors of poor outcomes. Neuroticism and (low) respiratory sinus arrhythmia (RSA) are risk factors of internalizing disorders that might predict increased psychopathology symptoms. The present study included 222 undergraduate students from [name removed] in Long Island, NY. Before the COVID-19 pandemic, participants completed self-report measures of neuroticism and internalizing symptoms and an electrocardiogram. Between April 15th to May 30th, 2020, participants again completed the measure of internalizing symptoms and a questionnaire about COVID-19 experiences. The COVID-19 pandemic was associated with increased distress, fear/obsessions, and (low) positive mood symptoms. There was a Neuroticism x RSA interaction in relation to distress symptoms, such that greater pre-COVID-19 neuroticism was associated with increased distress symptoms, but only in the context of low RSA. These findings suggest the COVID-19 pandemic has contributed to increased internalizing symptoms in young adults, and individuals with specific personality and autonomic risk factors may be at heightened risk for developing psychopathology.In the first week after the first COVID-19 patient was reported in the Netherlands, we conducted a pre-registered momentary assessment study (7 surveys per day, 50 participants, 7 days) to study the dynamic relationship between individuals' occupation with and worries about COVID-19 in daily life, and the moderating role of neuroticism in this relationship. At the group level, higher scores on occupation and worry co-occurred, and occupation predicted worry 1 h later, but not vice versa. There were substantial individual differences in the magnitudes and directions of the effects. For instance, occupation with COVID-19 was related to increases in worry for some but decreases in worry for others. BMS-986365 Neuroticism did not predict any of these individual differences in the links between worry and occupation. This study suggests that it is important to go beyond group-level analyses and to account for individual differences in responses to COVID-19.