Harnessing the power of synthetic data in healthcare: innovation, application, and privacy
Data-driven decision-making in modern healthcare underpins innovation and predictive
analytics in public health and clinical research. Synthetic data has shown promise in finance …
analytics in public health and clinical research. Synthetic data has shown promise in finance …
When AI meets additive manufacturing: Challenges and emerging opportunities for human-centered products development
Nowadays, additive manufacturing (AM) has been increasingly leveraged to produce human-
centered products, such as orthoses and prostheses as well as therapeutic helmets, finger …
centered products, such as orthoses and prostheses as well as therapeutic helmets, finger …
An empirical study of chronic diseases in the United States: a visual analytics approach to public health
W Raghupathi, V Raghupathi - International journal of environmental …, 2018 - mdpi.com
In this research we explore the current state of chronic diseases in the United States, using
data from the Centers for Disease Control and Prevention and applying visualization and …
data from the Centers for Disease Control and Prevention and applying visualization and …
HCI for health and wellbeing: Challenges and opportunities
A Blandford - International journal of human-computer studies, 2019 - Elsevier
Abstract In terms of Human–Computer Interaction, healthcare presents paradoxes: on the
one hand, there is substantial investment in innovative health technologies, particularly …
one hand, there is substantial investment in innovative health technologies, particularly …
The data-driven future of healthcare: a review
MM Amri, SA Abed - Mesopotamian Journal of Big Data, 2023 - mesopotamian.press
The future of disease detection, treatment, and prevention may very well lie in data-driven
healthcare. Here, we take stock of where things stand and highlight certain emerging issues …
healthcare. Here, we take stock of where things stand and highlight certain emerging issues …
European health data space—An opportunity now to grasp the future of data-driven healthcare
The May 2022 proposal from the European commission for a 'European health data
space'envisages advantages for health from exploiting the growing mass of health data in …
space'envisages advantages for health from exploiting the growing mass of health data in …
Smartphone-powered electrochemical biosensing dongle for emerging medical IoTs application
J Guo - IEEE Transactions on Industrial Informatics, 2017 - ieeexplore.ieee.org
Nowadays, the market of healthcare is experiencing a rapid growth and is believed to be
dramatically massive due to the upcoming global aging. The medical Internet of things (IoTs) …
dramatically massive due to the upcoming global aging. The medical Internet of things (IoTs) …
[HTML][HTML] RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses
The effort for combating the COVID-19 pandemic around the world has resulted in a huge
amount of data, eg, from testing, contact tracing, modelling, treatment, vaccine trials, and …
amount of data, eg, from testing, contact tracing, modelling, treatment, vaccine trials, and …
A systematic and universal artificial intelligence screening method for oropharyngeal dysphagia: improving diagnosis through risk management
A Martin-Martinez, J Miró, C Amadó, F Ruz, A Ruiz… - Dysphagia, 2023 - Springer
Oropharyngeal dysphagia (OD) is underdiagnosed and current screening is costly. We
aimed:(a) to develop an expert system (ES) based on machine learning that calculates the …
aimed:(a) to develop an expert system (ES) based on machine learning that calculates the …
RegressionExplorer: Interactive exploration of logistic regression models with subgroup analysis
D Dingen, M van't Veer, P Houthuizen… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
We present RegressionExplorer, a Visual Analytics tool for the interactive exploration of
logistic regression models. Our application domain is Clinical Biostatistics, where models …
logistic regression models. Our application domain is Clinical Biostatistics, where models …