Multimodal machine learning in precision health: A scoping review
Abstract Machine learning is frequently being leveraged to tackle problems in the health
sector including utilization for clinical decision-support. Its use has historically been focused …
sector including utilization for clinical decision-support. Its use has historically been focused …
[HTML][HTML] Multi-source information fusion: Progress and future
Abstract Multi-Source Information Fusion (MSIF), as a comprehensive interdisciplinary field
based on modern information technology, has gained significant research value and …
based on modern information technology, has gained significant research value and …
Recent advancements in emerging technologies for healthcare management systems: a survey
In recent times, the growth of the Internet of Things (IoT), artificial intelligence (AI), and
Blockchain technologies have quickly gained pace as a new study niche in numerous …
Blockchain technologies have quickly gained pace as a new study niche in numerous …
Real-time digital twins: Vision and research directions for 6G and beyond
This article presents a vision where real-time digital twins of the physical wireless
environments are continuously updated using multi-modal sensing data from the distributed …
environments are continuously updated using multi-modal sensing data from the distributed …
The role of machine learning and the internet of things in smart buildings for energy efficiency
Machine learning can be used to automate a wide range of tasks. Smart buildings, which
use the Internet of Things (IoT) to connect building operations, enable activities, such as …
use the Internet of Things (IoT) to connect building operations, enable activities, such as …
Cybersecurity awareness and education programs: a review of employee engagement and accountability
As organizations continue to grapple with the escalating threat landscape of cyber-attacks,
the imperative to fortify their cybersecurity defenses becomes increasingly paramount. This …
the imperative to fortify their cybersecurity defenses becomes increasingly paramount. This …
Backdoor attacks and defenses in federated learning: Survey, challenges and future research directions
Federated learning (FL) is an approach within the realm of machine learning (ML) that
allows the use of distributed data without compromising personal privacy. In FL, it becomes …
allows the use of distributed data without compromising personal privacy. In FL, it becomes …
Data-driven analytics leveraging artificial intelligence in the era of COVID-19: an insightful review of recent developments
A Majeed, SO Hwang - Symmetry, 2021 - mdpi.com
This paper presents the role of artificial intelligence (AI) and other latest technologies that
were employed to fight the recent pandemic (ie, novel coronavirus disease-2019 (COVID …
were employed to fight the recent pandemic (ie, novel coronavirus disease-2019 (COVID …
[PDF][PDF] Analyzing financial analysts' role in business optimization and advanced data analytics
TD Olorunyomi, TO Sanyaolu… - … Journal of Frontiers …, 2024 - researchgate.net
This paper explores the evolving role of financial analysts in business optimization, focusing
on their increasing reliance on advanced data analytics to drive strategic decision-making. It …
on their increasing reliance on advanced data analytics to drive strategic decision-making. It …
A prospective study: Advances in chaotic characteristics of serum Raman spectroscopy in the field of assisted diagnosis of disease
Y Liu, C Chen, X Tian, E Zuo, Z Cheng, Y Su… - Expert Systems with …, 2024 - Elsevier
Chaos theory is an important branch of mathematics and its theory has been widely applied
in many fields such as physics and medicine. Based on existing spectroscopic techniques …
in many fields such as physics and medicine. Based on existing spectroscopic techniques …