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Blockchain meets federated learning in healthcare: A systematic review with challenges and opportunities
Recently, innovations in the Internet of Medical Things (IoMT), information and
communication technologies, and machine learning (ML) have enabled smart healthcare …
communication technologies, and machine learning (ML) have enabled smart healthcare …
Intelligent healthcare: Integration of emerging technologies and Internet of Things for humanity
Health is gold, and good health is a matter of survival for humanity. The development of the
healthcare industry aligns with the development of humans throughout history. Nowadays …
healthcare industry aligns with the development of humans throughout history. Nowadays …
Review on security of federated learning and its application in healthcare
Artificial intelligence (AI) has led to a high rate of development in healthcare, and good
progress has been made on many complex medical problems. However, there is a lack of …
progress has been made on many complex medical problems. However, there is a lack of …
[HTML][HTML] Internet of robotic things for mobile robots: concepts, technologies, challenges, applications, and future directions
Abstract Nowadays, Multi Robotic System (MRS) consisting of different robot shapes, sizes
and capabilities has received significant attention from researchers and are being deployed …
and capabilities has received significant attention from researchers and are being deployed …
Handling privacy-sensitive medical data with federated learning: challenges and future directions
Recent medical applications are largely dominated by the application of Machine Learning
(ML) models to assist expert decisions, leading to disruptive innovations in radiology …
(ML) models to assist expert decisions, leading to disruptive innovations in radiology …
Federated learning for medical image analysis with deep neural networks
S Nazir, M Kaleem - Diagnostics, 2023 - mdpi.com
Medical image analysis using deep neural networks (DNN) has demonstrated state-of-the-
art performance in image classification and segmentation tasks, aiding disease diagnosis …
art performance in image classification and segmentation tasks, aiding disease diagnosis …
Federated learning for healthcare applications
Due to the fast advancement of artificial intelligence (AI), centralized-based models have
become critical for healthcare tasks like in medical image analysis and human behavior …
become critical for healthcare tasks like in medical image analysis and human behavior …
Integrated CNN and federated learning for COVID-19 detection on chest X-ray images
Currently, Coronavirus Disease 2019 (COVID-19) is still endangering world health and
safety and deep learning (DL) is expected to be the most powerful method for efficient …
safety and deep learning (DL) is expected to be the most powerful method for efficient …
Dres-fl: Dropout-resilient secure federated learning for non-iid clients via secret data sharing
Federated learning (FL) strives to enable collaborative training of machine learning models
without centrally collecting clients' private data. Different from centralized training, the local …
without centrally collecting clients' private data. Different from centralized training, the local …
Data-driven analytics leveraging artificial intelligence in the era of COVID-19: an insightful review of recent developments
A Majeed, SO Hwang - Symmetry, 2021 - mdpi.com
This paper presents the role of artificial intelligence (AI) and other latest technologies that
were employed to fight the recent pandemic (ie, novel coronavirus disease-2019 (COVID …
were employed to fight the recent pandemic (ie, novel coronavirus disease-2019 (COVID …