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Blockchain is a systematic data registration mechanism that makes the system difficult or impossible to hack, change or cheat.A blockchain is a chain consisting of a complete ledger or database of all transactions that can be publicly distributed to all users. In dentistry, blockchain technology is protective and trustworthy to exchange data to preserve patient information and transactions. This helps to turn the bulkier paper records into a digital archive that can be accessed internationally and helps the dentist, patients, and colleagues. It is commonly used in different industries, such as the food industry, medical health care, forensics, banking, etc. This technology can integrate various workflows and allows patients to preserve good dental health and also enables patients or participants to make simple transactions without a third party. This paper discusses how this technology can be used in the management of patient records, holding appointments, cashless payment transactions, confidential transfer of patient reports to the specialized dentist during and after the pandemic situation of Covid 19. © 2022, Suranaree Journal of Science and Technology. All Rights Reserved.
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Background: SARS-COV-2 is also known as coronavirus causes an infectious disease has caused a global concern due to its pandemic nature. In India, nearly 36 million cases and 5.1 lakh deaths have been recorded so far. Laboratory biomarkers play an important role in improving the clinical situational awareness by predicting risk stratification and by discriminating between severe and non-severe cases. There is no sufficient information available regarding the role of C-reactive protein (CRP), lactate dehydrogenase (LDH), Vitamin D, and interleukin-6 (IL-6) in the prognosis of COVID-19 patients in Southern part of India. Aims and Objectives: We aim to retrospectively analyze CRP, LDH, Vitamin D, and IL-6 in COVID-19 patients. Materials and Methods: The observational and retrospective study was carried out from the case records of 103 patients from November 2021 to February 2022 in which CRP, LDH, Vitamin D, IL-6, COVID-19 Reporting and Data System (CO-RADS), and CT sore were analyzed during admission and follow-up period in the hospital. Mean, mean difference, standard deviation, standard error difference, and P value were calculated. P<0.05 was considered to be significant. Results: CRP, LDH, IL-6, Vitamin D, CO-RADS, and CT score were decreased during the follow-up period when these levels were compared at the time of admission in the hospital, while there is an increase in Vitamin D levels during the follow-up period. Conclusion: The use of reliable and easy to use assays such as CRP, LDH, Vitamin D, and IL-6 plays an important role in the diagnosis and prognosis of COVID-19. [ FROM AUTHOR] Copyright of Asian Journal of Medical Sciences is the property of Manipal Colleges of Medical Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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Heart disease is a major concern for the medical fraternity under the influence of global pandemic outbreak. According to WHO 17.9 million deaths are reported due to suffering from cardio disease related medical influences and has increased due to comorbidities in outbreak of SARS-CoVID-19 globally. In this research, a focus is on proposing a technique to deal with a predict cognitive approach of classifying and validating the heat diseases risks. The technique is aided with SVM based classifier for decision support via risk factor validation. The technique has provided an improved predictive accuracy and reliability over the risk factor validation caused due to pandemic parameters. © 2021 IEEE.
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A novel COVID-19 caused by the virus SARS-CoV-2 was identified at China in December 2019, and it was declared as global pandemic on 11th March 2020 by the World Health Organization. In India on 30th January 2020, the first COVID-19 case was confirmed at Kerala. As of 6th June 2020, 6,702,662 cases have been reported in India even though stringent nationwide lockdown has been implemented. It is essential to identify the rate of disease transmission and its characterization. ICMR stated that 80% of COVID patients in India are without symptoms. In that case, we should focus on identifying the optimal attributes that will give the rate of transmission of this disease. Statistical machine learning is a powerful tool to fight against COVID-19 which gives the potential models for identifying the pattern of this disease, predictive analysis, and rate of transmission. This chapter aims to construct the predictive model to identify the severity of this disease transmission and also find the topographical spread of the contagion. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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COVID-19 is an epidemic that has been multiplying rapidly across the globe. To order to regulate its growth, several nations have implemented home-stay or lockout policies. Prolonged domestic residency, though, can cause worse effects such as economic instability, homelessness, food shortages and individuals' mental health issues. This article presents an intelligent consumer electronics solution for secure & gradual launch after residence restrictions have been lifted. Completely automatic hand sanitizer supplier to prevent quickly spreading novel corona virus. It is implemented to restrict the development of new positive cases through auto touch tracking and by promoting critical social distancing.