Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Machine and Deep Learning Towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions
16
Zitationen
1
Autoren
2020
Jahr
Abstract
Machine Learning (ML) and Deep Learning (DL) have been widely used in our daily lives in a variety of ways with many effective stories. Also, they have been instrumental in tackling the Coronavirus (COVID-19) epidemic, which has been occurring around the world. The COVID-19 epidemic caused by the SARS-CoV-2 virus has spread rapidly around the world, leading to global outbreaks. Most governments, businesses, and scientific research institutions are taking part in the COVID-19 struggle to stem the spread of the disease. In this survey, we investigate the Artificial Intelligence (AI) based ML and DL towards COVID-19 diagnosis and treatment. In addition, we summarize the AI-based ML and DL methods and available datasets, resources, and results in the fight against COVID-19. This survey provides the ML and DL researchers and the wider health community a comprehensive overview of the current state-of-the-art methodologies and applications with details of how ML and DL and data can improve the status of COVID-19, and further studies to stop the COVID-19 outbreak. Challenges and future directions details are also provided.
Ähnliche Arbeiten
Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study
2020 · 22.609 Zit.
La certeza de lo impredecible: Cultura Educación y Sociedad en tiempos de COVID19
2020 · 19.271 Zit.
A Multi-Modal Distributed Real-Time IoT System for Urban Traffic Control (Invited Paper)
2024 · 14.254 Zit.
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
2018 · 8.506 Zit.
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
2021 · 7.118 Zit.