[HTML][HTML] A survey of multimodal information fusion for smart healthcare: Mapping the journey from data to wisdom

T Shaik, X Tao, L Li, H Xie, JD Velásquez - Information Fusion, 2024 - Elsevier
Multimodal medical data fusion has emerged as a transformative approach in smart
healthcare, enabling a comprehensive understanding of patient health and personalized …

Enhancing digital health services with big data analytics

N Berros, F El Mendili, Y Filaly… - Big data and cognitive …, 2023 - mdpi.com
Medicine is constantly generating new imaging data, including data from basic research,
clinical research, and epidemiology, from health administration and insurance …

[HTML][HTML] Reimagining Core Entrustable Professional Activities for Undergraduate Medical Education in the Era of Artificial Intelligence

SM Jacobs, NN Lundy, SB Issenberg… - JMIR Medical …, 2023 - mededu.jmir.org
The proliferation of generative artificial intelligence (AI) and its extensive potential for
integration into many aspects of health care signal a transformational shift within the health …

An integrating computing framework based on edge-fog-cloud for internet of healthcare things applications

QV Khanh, NV Hoai, AD Van, QN Minh - Internet of Things, 2023 - Elsevier
History has demonstrated that healthcare and medical systems play a crucial role in
enforcing the development of science and technology. Humans have been seeing an …

Multi model implementation on general medicine prediction with quantum neural networks

SA Kumar, A Kumar, V Dutt… - 2021 Third International …, 2021 - ieeexplore.ieee.org
Medical is the large-scale repository where there is more chances to create a new model in
the zone of prediction. The proposed methodology mentioned in this article speaks about …

A systematic review on big data applications and scope for industrial processing and healthcare sectors

K Rahul, RK Banyal, N Arora - Journal of Big Data, 2023 - Springer
Nowadays, big data is an emerging area of computer science. Data are generated through
different sources such as social media, e-commerce, blogs, banking, healthcare …

Sanitizing data for analysis: Designing systems for data understanding

J Holstein, M Schemmer, J Jakubik, M Vössing… - Electronic Markets, 2023 - Springer
As organizations accumulate vast amounts of data for analysis, a significant challenge
remains in fully understanding these datasets to extract accurate information and generate …

Machine learning and big data implementation on health care data

G Sasubilli, A Kumar - 2020 4th International Conference on …, 2020 - ieeexplore.ieee.org
Healthcare is the most prominent field suitable for the applications of machine learning and
big data on health care data. The implementations of health care with big data and machine …

Industry 4.0 and healthcare: Context, applications, benefits and challenges

K Kotzias, FA Bukhsh, JJ Arachchige, M Daneva… - Iet …, 2023 - Wiley Online Library
Industry 4.0 refers to the digital transformation in the manufacturing domain through new
technology. Currently, it expands well beyond manufacturing, affecting many areas of life …

Context-aware big data quality assessment: a scoping review

H Fadlallah, R Kilany, H Dhayne, R El Haddad… - ACM Journal of Data …, 2023 - dl.acm.org
The term data quality refers to measuring the fitness of data regarding the intended usage.
Poor data quality leads to inadequate, inconsistent, and erroneous decisions that could …