Data drift in medical machine learning: implications and potential remedies

B Sahiner, W Chen, RK Samala… - The British Journal of …, 2023 - academic.oup.com
Data drift refers to differences between the data used in training a machine learning (ML)
model and that applied to the model in real-world operation. Medical ML systems can be …

Review on COVID‐19 diagnosis models based on machine learning and deep learning approaches

ZAA Alyasseri, MA Al‐Betar, IA Doush… - Expert …, 2022 - Wiley Online Library
COVID‐19 is the disease evoked by a new breed of coronavirus called the severe acute
respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Recently, COVID‐19 has become a …

Impact of generative artificial intelligence models on the performance of citizen data scientists in retail firms

RA Abumalloh, M Nilashi, KB Ooi, GWH Tan… - Computers in …, 2024 - Elsevier
Abstract Generative Artificial Intelligence (AI) models serve as powerful tools for
organizations aiming to integrate advanced data analysis and automation into their …

Federated learning for COVID-19 detection with generative adversarial networks in edge cloud computing

DC Nguyen, M Ding, PN Pathirana… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
COVID-19 has spread rapidly across the globe and become a deadly pandemic. Recently,
many artificial intelligence-based approaches have been used for COVID-19 detection, but …

Quantum computing and machine learning for Arabic language sentiment classification in social media

A Omar, T Abd El-Hafeez - Scientific Reports, 2023 - nature.com
With the increasing amount of digital data generated by Arabic speakers, the need for
effective and efficient document classification techniques is more important than ever. In …

[HTML][HTML] Machine learning sensors for diagnosis of COVID-19 disease using routine blood values for internet of things application

A Velichko, MT Huyut, M Belyaev, Y Izotov, D Korzun - Sensors, 2022 - mdpi.com
Healthcare digitalization requires effective applications of human sensors, when various
parameters of the human body are instantly monitored in everyday life due to the Internet of …

Bias in algorithms of AI systems developed for COVID-19: A sco** review

J Delgado, A de Manuel, I Parra, C Moyano… - Journal of bioethical …, 2022 - Springer
To analyze which ethically relevant biases have been identified by academic literature in
artificial intelligence (AI) algorithms developed either for patient risk prediction and triage, or …

Predictive models of long COVID

B Antony, H Blau, E Casiraghi, JJ Loomba… - …, 2023 - thelancet.com
Background The cause and symptoms of long COVID are poorly understood. It is
challenging to predict whether a given COVID-19 patient will develop long COVID in the …

Predicting COVID-19 vaccination intention: the determinants of vaccine hesitancy

N Fernandes, D Costa, D Costa, J Keating, J Arantes - Vaccines, 2021 - mdpi.com
Do people want to be vaccinated against COVID-19? Herd immunity is dependent on
individuals' willingness to be vaccinated since vaccination is not mandatory. Our main goal …

[HTML][HTML] Resilient artificial intelligence in health: synthesis and research agenda toward next-generation trustworthy clinical decision support

C Sáez, P Ferri, JM García-Gómez - Journal of Medical Internet Research, 2024 - jmir.org
Artificial intelligence (AI)–based clinical decision support systems are gaining momentum by
relying on a greater volume and variety of secondary use data. However, the uncertainty …