Forecasting the spread of COVID-19 using LSTM network - Kumar, Shiu; Sharma, Ronesh; Tsunoda, Tatsuhiko; Kumarevel, Thirumananseri; Sharma, Alok (BMC bioinformatics, 2021)
Keywords: Air pollution; Algorithms; Bioinformatics; Biomedical and Life Sciences; Communicable Disease Control; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Control; Coronaviruses; COVID-19; COVID-19 vaccines; Decision making; Disease prevention; Disease transmission; Economic impact; End date prediction; Epidemics; Forecasting; Forecasts and trends; Government industry relations; Humans; Impact analysis; Infections; Life Sciences; Long short-term memory; Long short-term memory (LSTM); Machine learning; Mathematical models; Microarrays; Neural networks; New Zealand; Outdoor air quality; Pandemic; Pandemics; Prediction models; SARS-CoV-2; Severe acute respiratory syndrome; Severe acute respiratory syndrome coronavirus 2; Shutdowns; Viral diseases; New Zealand; Saudi Arabia; Canada; Italy; India; COVID-19; Pandemic; Long short-term memory (LSTM); End date prediction