Machine learning, infection, microbial toxins profile and health monitoring pre/post general surgeries during COVID-۱۹ pandemic
سال انتشار: 1401
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 111
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شناسه ملی سند علمی:
JR_JCBIOR-3-3_001
تاریخ نمایه سازی: 27 بهمن 1403
چکیده مقاله:
Although almost ۲ years have passed since the beginning of the coronavirus disease ۲۰۱۹ (COVID-۱۹) pandemic in the world, there is still a threat to the health of people at risk and patients. Specialists in various sciences conduct various research in order to eliminate or reduce the problems caused by this disease. Surgery is one of the sciences that plays a critical role in this regard. Both physicians and patients should pay attention to the potent steps of different infections’ key-points during pre/post-general surgeries in the case of preventing or accelerating the healing process of nosocomial acquired COVID-۱۹. The relationship between COVID-۱۹ and general surgical events is one of the factors that could directly or indirectly play a key role in the body's resilience to COVID-۱۹. In this article, we introduce a link between pre/post-general surgery steps, human microbial toxin profiles, and the incidence of acquired COVID-۱۹ in patients. In linking the components of this network, artificial intelligence (AI), machine learning (ML) and data mining (DM) can be important strategies to assist health providers in choosing the best decision based on a patient’s history.
کلیدواژه ها:
نویسندگان
Mohammad Javad Mohammadi
۱Medical School, Islamic Azad University, Sari Branch, Sari, Iran
Kiana Aslanimehr
۲Qazvin University of Medical Sciences, Qazvin, Iran