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Data drift in medical machine learning: implications and potential remedies
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 …
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
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 …
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
Abstract Generative Artificial Intelligence (AI) models serve as powerful tools for
organizations aiming to integrate advanced data analysis and automation into their …
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
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 …
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 …
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 …
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
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 …
artificial intelligence (AI) algorithms developed either for patient risk prediction and triage, or …
Predictive models of long COVID
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 …
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
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 …
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
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 …
relying on a greater volume and variety of secondary use data. However, the uncertainty …