2020/04/03 by Babacar Mbaye Ndiaye, Ndiaye, Babacar Mbaye, Lena Tendeng +3 · 3 citations
Computer Science · Medicine · #Anomaly Detection Techniques and Applications #COVID-19 diagnosis using AI #Computational Physics and Python Applications #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Populations and Evolution (q-bio.PE)
paper · pdf · doi:10.48550/arxiv.2004.01574
openalex publication_date 2020/04/03 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
This work is a trial in which we propose SIR model and machine learning tools\nto analyze the coronavirus pandemic in the real world. Based on the public data\nfrom citedatahub, we estimate main key pandemic parameters and make\npredictions on the inflection point and possible ending time for the real world\nand specifically for Senegal. The coronavirus disease 2019, by World Health\nOrganization, rapidly spread out in the whole China and then in the whole\nworld. Under optimistic estimation, the pandemic in some countries will end\nsoon, while for most part of countries in the world (US, Italy, etc.), the hit\nof anti-pandemic will be no later than the end of April.\n