[HTML][HTML] Application of uncertainty quantification to artificial intelligence in healthcare: A review of last decade (2013–2023)
Uncertainty estimation in healthcare involves quantifying and understanding the inherent
uncertainty or variability associated with medical predictions, diagnoses, and treatment …
uncertainty or variability associated with medical predictions, diagnoses, and treatment …
[HTML][HTML] A survey of multimodal information fusion for smart healthcare: Mapping the journey from data to wisdom
Multimodal medical data fusion has emerged as a transformative approach in smart
healthcare, enabling a comprehensive understanding of patient health and personalized …
healthcare, enabling a comprehensive understanding of patient health and personalized …
[HTML][HTML] A systematic review of data fusion techniques for optimized structural health monitoring
Advancements in structural health monitoring (SHM) techniques have spiked in the past few
decades due to the rapid evolution of novel sensing and data transfer technologies. This …
decades due to the rapid evolution of novel sensing and data transfer technologies. This …
Secure IoMT for disease prediction empowered with transfer learning in healthcare 5.0, the concept and case study
Identifying human diseases remains a difficult process, even in the age of advanced
information technology and the smart healthcare industry 5.0. In the smart healthcare …
information technology and the smart healthcare industry 5.0. In the smart healthcare …
Fused weighted federated deep extreme machine learning based on intelligent lung cancer disease prediction model for healthcare 5.0
In the era of advancement in information technology and the smart healthcare industry 5.0,
the diagnosis of human diseases is still a challenging task. The accurate prediction of …
the diagnosis of human diseases is still a challenging task. The accurate prediction of …
Interpretable machine learning for personalized medical recommendations: A LIME-based approach
Y Wu, L Zhang, UA Bhatti, M Huang - Diagnostics, 2023 - mdpi.com
Chronic diseases are increasingly major threats to older persons, seriously affecting their
physical health and well-being. Hospitals have accumulated a wealth of health-related data …
physical health and well-being. Hospitals have accumulated a wealth of health-related data …
IoT-enabled fault prediction and maintenance for smart charging piles
H Dui, X Dong, L Chen, Y Wang - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
With the application of the Internet of Things (IoT), smart charging piles, which are important
facilities for new energy electric vehicles (NEVs), have become an important part of the …
facilities for new energy electric vehicles (NEVs), have become an important part of the …
An intelligent diabetic patient tracking system based on machine learning for E-health applications
Background: Continuous surveillance helps people with diabetes live better lives. A wide
range of technologies, including the Internet of Things (IoT), modern communications, and …
range of technologies, including the Internet of Things (IoT), modern communications, and …
Diabetic retinopathy detection: A blockchain and African vulture optimization algorithm-based deep learning framework
P Uppamma, S Bhattacharya - Electronics, 2023 - mdpi.com
Blockchain technology has gained immense momentum in the present era of information
and digitalization and is likely to gain extreme popularity among the next generation, with …
and digitalization and is likely to gain extreme popularity among the next generation, with …
Cyber security event detection using machine learning technique
SM Muneer, MB Alvi, A Farrakh - International Journal of Computational …, 2023 - ijcis.com
Artificial Intelligence and Machine Learning techniques have become crucial components in
the field of cybersecurity. The proposed model you mentioned can help to enhance the …
the field of cybersecurity. The proposed model you mentioned can help to enhance the …