2D Anatomical Structure for COVID-19 Medical Images.

For many clinical goals like surgical planning and radiotherapy treatment planning is necessary to understand the anatomical structures of the organ that is targeted. At the same time the 2D/3D shape of the organ is important to be reconstructed for the benefit of the doctors. For that reason, accurate segmentation techniques must be proposed to overcome the big data medical image storage problem. The main purpose of this work is to apply segmentation techniques for the definition of 3D organs (anatomical structures) when big data information has been stored and must be organized by the doctors for medical diagnosis. The processes would be implemented in the CT images from patients with COVID-19.

The Contribution of Informatics to Overcoming the Covid-19 Fake News Outbreak by Learning to Navigate the Infodemic.

Daily, people are being exposed to an enormous amount of Covid-19 information, but not all of it is reliable. This phenomenon seriously affects the public health policy effectiveness, because there is a lot of misleading or inaccurate information, which is spreading rapidly and makes it more difficult to restrict the pandemic. Healthcare informatics has emerged as a diverse and important new field. Healthcare informatics applications are becoming more and more popular and are providing easy access to new sources of knowledge. This way, the quality of patient care will improve and productivity will increase. However, people should also learn how to navigate this infodemic properly.

Machine Learning to Identify Fake News for COVID-19.

International Organizations are seriously concerned about the fake news phenomenon. UNESCO has defined the term of misinformation/disinformation, which are the two faces of fake news. European Commission has conducted a survey about "Fake News" through EU citizens to estimate the awareness and people behaviour related to the appearance of fake news and disinformation on electronic. The findings are quite worrying, since about 40% come across fake news daily and 85% evaluate fake news as a problem. The aim of this work is to introduce an Artificial Intelligence approach, the Decision Trees algorithm to identify fake news on the COVID-19.

Sleep and Motion Disorders of Physicians and Nurses Working in Hospitals Facing the Pandemic of COVID 19.

INTRODUCTION: Several research studies have started to investigate the health conditions of medical doctors and nurses in order to find a relationship if any between their work environment, their usually heavy duties and the result of these two parametric on patients' health. AIM: The present research study is an effort to investigate the relationship between the physical activity and sleep disorders among health care professionals, particularly among medical doctors and nurses. METHODS: Participants of the study were asked to fill a questionnaire which was a mixture of other internationally accredited questionnaires regarding physical activity level as well as sleeping functions. Data were collected among 204 physicians and nurses. The statistical analysis revealed a correlation between physical activity and some aspects of sleep disorders. RESULTS: A total number of 204 questionnaires have been distributed to medical doctors and nurses working in public hospitals in Athens Greece from the middle of February until the middle of April 2020. The hospitals were assigned by the health authorities to the fight of the pandemic of COVID 19. The majority of the participants were women 71,3% and 28,7% were men. From a total of 204 half of them were medical doctors and half of them were nurses. 43% were married, 49% were single and 8% were divorced and there were no widows. Regarding the participant nurses, 43% had a university degree and 38,4% had a technological education degree. The results of the statistical analysis showed that there are positive correlations between the level of physical activity during the daily work and the free time of the participants with parameters that are related to sleep disorders. CONCLUSION: The sample of the study was not a large one but nevertheless a stressful situation such as is the epidemic of COVID19 can provide useful information in order to better understand the relationship between physical activity and sleeping disorders in such working conditions.

Epidemiological Analysis of the Covid-19 Epidemic in Greece.

During the last months the Coronavirus disease 2019 (COVID-2019) has been recognized as a global threat. Transmission of the infection has rapidly increased in Europe as well as in Greece, living behind a huge number of deaths. During this situation an analysis of the spread of the disease must be undertaken and characteristics of the virus must be recognized. For the analysis of the impact of the disease in the population during this time period, epidemiological indexes have been introduced.

Remote Monitoring of Patients in Quarantine in the Era of SARS-CoV-2 Pandemic.

The aim of our study is to propose a remote patient monitoring solution through a smart phone application (Smart Patient) collecting health data to support diagnosis, monitoring and predicting poor outcome in asymptomatic/mild cases of COVID-19, including signs and symptoms, risk factors, comorbidities, medications and vital signs such as body temperature, respiratory rate, heart rate and oxygen saturation. By continuous daily recording of suspected cases and patients, family doctors in the community will be able to follow up cases and intervene promptly when deterioration in vital signs and symptoms takes place referring the patient to the hospital.