چکیده مقاله
This study examines the applications and Deep Learning ML algorithms utilized in the COVID ۱۹ investigation and other contexts Researchers and authorities have focused more on basic statistical and epidemiological methodology than the conventional methods for COVID ۱۹ worldwide epidemic prediction One of the main obstacles to stopping the development of COVID ۱۹ is the inadequate lack of medical tests for detecting and finding a cure To address this issue, a few statistically based enhancements are being reinforced, leading to a partial resolution to a specific degree ML has pushed for a wide range of intelligence based strategies, methods, and tools to address the medical business's problems This work has examined how innovative structures like machine learning may be used to manage COVID ۱۹ related epidemic challenges This study's primary objective is to Analyze the effects of the COVID ۱۹ data type
کلیدواژهها
نویسندگان
Farzane Tajidini
Tabarestan University of Chalus, Chalus, Iran
Raziye Mehri
۲ Deputy of Research and Technology, Ardabil University of Medical Sciences, Ardabil, Iran ۳ Department of Community Medicine, Faculty of Medicine, Ardabil University of Medical Science, Ardabil, Iran
شیوه ارجاع
Tajidini، Farzane و Mehri، Raziye،1401،A survey of using Deep learning algorithms for the Covid-۱۹ (SARS-CoV-۲) pandemic: A review،نهمین کنگره ملی تازه های مهندسی برق و کامپیوتر ایران،تهران
ارائهشده در
یازدهمین کنگره ملی مهندسی برق و کامپیوتر ایران با تاکید بر فن آوری های بومی ایران20 بهمن 1405 تا 21 بهمن 1405 · تهران