Machine learning: Algorithms, real-world applications and research directions
IH Sarker - SN computer science, 2021 - Springer
In the current age of the Fourth Industrial Revolution (4 IR or Industry 4.0), the digital world
has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data …
has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data …
[HTML][HTML] Adoption of digital technologies in health care during the COVID-19 pandemic: systematic review of early scientific literature
Background The COVID-19 pandemic is favoring digital transitions in many industries and in
society as a whole. Health care organizations have responded to the first phase of the …
society as a whole. Health care organizations have responded to the first phase of the …
Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM
COVID-19, responsible of infecting billions of people and economy across the globe,
requires detailed study of the trend it follows to develop adequate short-term prediction …
requires detailed study of the trend it follows to develop adequate short-term prediction …
The role of machine learning techniques in internet of things-based cloud applications
S Mishra, AK Tyagi - Artificial intelligence-based internet of things systems, 2022 - Springer
Abstract Today's Machine Learning (ML) in a blend with Internet of Things (IoT)-based cloud
applications plays a significant role in our everyday life. As indicated by Gartner's recent …
applications plays a significant role in our everyday life. As indicated by Gartner's recent …
Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey
S Bhattacharya, PKR Maddikunta, QV Pham… - Sustainable cities and …, 2021 - Elsevier
Since December 2019, the coronavirus disease (COVID-19) outbreak has caused many
death cases and affected all sectors of human life. With gradual progression of time, COVID …
death cases and affected all sectors of human life. With gradual progression of time, COVID …
COVID-19 cases prediction by using hybrid machine learning and beetle antennae search approach
The main objective of this paper is to further improve the current time-series prediction
(forecasting) algorithms based on hybrids between machine learning and nature-inspired …
(forecasting) algorithms based on hybrids between machine learning and nature-inspired …
[HTML][HTML] Comparative analysis of Gated Recurrent Units (GRU), long Short-Term memory (LSTM) cells, autoregressive Integrated moving average (ARIMA), seasonal …
Several machine learning and deep learning models were reported in the literature to
forecast COVID-19 but there is no comprehensive report on the comparison between …
forecast COVID-19 but there is no comprehensive report on the comparison between …
Federated learning for COVID-19 screening from Chest X-ray images
Today, the whole world is facing a great medical disaster that affects the health and lives of
the people: the COVID-19 disease, colloquially known as the Corona virus. Deep learning is …
the people: the COVID-19 disease, colloquially known as the Corona virus. Deep learning is …
Forecasting the dynamics of cumulative COVID-19 cases (confirmed, recovered and deaths) for top-16 countries using statistical machine learning models: Auto …
Most countries are reopening or considering lifting the stringent prevention policies such as
lockdowns, consequently, daily coronavirus disease (COVID-19) cases (confirmed …
lockdowns, consequently, daily coronavirus disease (COVID-19) cases (confirmed …
COVID-19 pandemic prediction for Hungary; a hybrid machine learning approach
Several epidemiological models are being used around the world to project the number of
infected individuals and the mortality rates of the COVID-19 outbreak. Advancing accurate …
infected individuals and the mortality rates of the COVID-19 outbreak. Advancing accurate …