Federated learning for smart cities: A comprehensive survey
With the advent of new technologies such as the Artificial Intelligence of Things (AIoT), big
data, fog computing, and edge computing, smart city applications have suffered from issues …
data, fog computing, and edge computing, smart city applications have suffered from issues …
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 …
On the opportunities and risks of foundation models
AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
Aging in COVID-19: Vulnerability, immunity and intervention
The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic was first
reported in Wuhan, China in December 2019, moved across the globe at an unprecedented …
reported in Wuhan, China in December 2019, moved across the globe at an unprecedented …
The applications of MCDM methods in COVID-19 pandemic: A state of the art review
A Sotoudeh-Anvari - Applied Soft Computing, 2022 - Elsevier
Likened to the economic calamity of World War Two, the COVID-19 pandemic has sparked
fears of a deep economic crisis, killed more than six million people worldwide and had a …
fears of a deep economic crisis, killed more than six million people worldwide and had a …
Internet of medical things (IoMT): Overview, emerging technologies, and case studies
S Razdan, S Sharma - IETE technical review, 2022 - Taylor & Francis
In the Internet of Medical Things (IoMT), the Internet of Things (IoT) is integrated with medical
devices, enabling improved patient comfort, cost-effective medical solutions, quick hospital …
devices, enabling improved patient comfort, cost-effective medical solutions, quick hospital …
[HTML][HTML] Machine learning-based approach: Global trends, research directions, and regulatory standpoints
R Pugliese, S Regondi, R Marini - Data Science and Management, 2021 - Elsevier
The field of machine learning (ML) is sufficiently young that it is still expanding at an
accelerating pace, lying at the crossroads of computer science and statistics, and at the core …
accelerating pace, lying at the crossroads of computer science and statistics, and at the core …
ANTi-Vax: a novel Twitter dataset for COVID-19 vaccine misinformation detection
Abstract Objectives COVID-19 (SARS-CoV-2) pandemic has infected hundreds of millions
and inflicted millions of deaths around the globe. Fortunately, the introduction of COVID-19 …
and inflicted millions of deaths around the globe. Fortunately, the introduction of COVID-19 …
Review on COVID‐19 diagnosis models based on machine learning and deep learning approaches
COVID‐19 is the disease evoked by a new breed of coronavirus called the severe acute
respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Recently, COVID‐19 has become a …
respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Recently, COVID‐19 has become a …
Advances in de novo drug design: from conventional to machine learning methods
De novo drug design is a computational approach that generates novel molecular structures
from atomic building blocks with no a priori relationships. Conventional methods include …
from atomic building blocks with no a priori relationships. Conventional methods include …