Multimodal machine learning in precision health: A scoping review

A Kline, H Wang, Y Li, S Dennis, M Hutch, Z Xu… - npj Digital …, 2022 - nature.com
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 …

[HTML][HTML] Multi-source information fusion: Progress and future

LI Xinde, F Dunkin, J Dezert - Chinese Journal of Aeronautics, 2024 - Elsevier
Abstract Multi-Source Information Fusion (MSIF), as a comprehensive interdisciplinary field
based on modern information technology, has gained significant research value and …

Recent advancements in emerging technologies for healthcare management systems: a survey

SB Junaid, AA Imam, AO Balogun, LC De Silva… - Healthcare, 2022 - mdpi.com
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 …

Real-time digital twins: Vision and research directions for 6G and beyond

A Alkhateeb, S Jiang, G Charan - IEEE Communications …, 2023 - ieeexplore.ieee.org
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 …

The role of machine learning and the internet of things in smart buildings for energy efficiency

SFA Shah, M Iqbal, Z Aziz, TA Rana, A Khalid… - Applied Sciences, 2022 - mdpi.com
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 …

Cybersecurity awareness and education programs: a review of employee engagement and accountability

TO Abrahams, OA Farayola, S Kaggwa… - Computer Science & IT …, 2024 - fepbl.com
As organizations continue to grapple with the escalating threat landscape of cyber-attacks,
the imperative to fortify their cybersecurity defenses becomes increasingly paramount. This …

Backdoor attacks and defenses in federated learning: Survey, challenges and future research directions

TD Nguyen, T Nguyen, P Le Nguyen, HH Pham… - … Applications of Artificial …, 2024 - Elsevier
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 …

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 …

[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 …

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 …