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COVID-19-associated mucormycosis and treatments 被引量:2
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作者 Vetriselvan Subramaniyan Shivkanya Fuloria +12 位作者 Hari Kumar Darnal Dhanalekshmi Unnikrishnan Meenakshi Mahendran Sekar Rusli Bin Nordin Srikumar Chakravarthi Kathiresan V.Sathasivam Shah Alam Khan Yuan Seng Wu Usha Kumari Kalvatala Sudhakar rishabha malviya Vipin Kumar Sharma Neeraj Kumar Fuloria 《Asian Pacific Journal of Tropical Medicine》 SCIE CAS 2021年第9期401-409,共9页
In the current pandemic,COVID-19 patients with predisposing factors are at an increased risk of mucormycosis,an uncommon angioinvasive infection that is caused by fungi with Mucor genus which is mainly found in plants... In the current pandemic,COVID-19 patients with predisposing factors are at an increased risk of mucormycosis,an uncommon angioinvasive infection that is caused by fungi with Mucor genus which is mainly found in plants and soil.Mucormycosis development in COVID-19 patient is related to various factors,such as diabetes,immunocompromise and neutropenia.Excessive use of glucocorticoids for the treatment of critically ill COVID-19 patients also leads to opportunistic infections,such as pulmonary aspergillosis.COVID-19 patients with mucormycosis have a very high mortality rate.This review describes the pathogenesis and various treatment approaches for mucormycosis in COVID-19 patients,including medicinal plants,conventional therapies,adjunct and combination therapies. 展开更多
关键词 MUCORMYCOSIS COVID-19 IMMUNOSUPPRESSION PATHOGENESIS Treatment
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Challenges and opportunities of big data analytics in healthcare
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作者 Priyanshi Goyal rishabha malviya 《Health Care Science》 2023年第5期328-338,共11页
Data science is an interdisciplinary discipline that employs big data,machine learning algorithms,data mining techniques,and scientific methodologies to extract insights and information from massive amounts of structu... Data science is an interdisciplinary discipline that employs big data,machine learning algorithms,data mining techniques,and scientific methodologies to extract insights and information from massive amounts of structured and unstructured data.The healthcare industry constantly creates large,important databases on patient demographics,treatment plans,results of medical exams,insurance coverage,and more.The data that IoT(Internet of Things)devices collect is of interest to data scientists.Data science can help with the healthcare industry's massive amounts of disparate,structured,and unstructured data by processing,managing,analyzing,and integrating it.To get reliable findings from this data,proper management and analysis are essential.This article provides a comprehen-sive study and discussion of process data analysis as it pertains to healthcare applications.The article discusses the advantages and dis-advantages of using big data analytics(BDA)in the medical industry.The insights offered by BDA,which can also aid in making strategic decisions,can assist the healthcare system. 展开更多
关键词 big data analytics healthcare SURVEILLANCE TECHNOLOGY patient care
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