Machine learning for healthcare wearable devices: the big picture
Using artificial intelligence and machine learning techniques in healthcare applications has
been actively researched over the last few years. It holds promising opportunities as it is …
been actively researched over the last few years. It holds promising opportunities as it is …
[HTML][HTML] Privacy-preserving artificial intelligence in healthcare: Techniques and applications
There has been an increasing interest in translating artificial intelligence (AI) research into
clinically-validated applications to improve the performance, capacity, and efficacy of …
clinically-validated applications to improve the performance, capacity, and efficacy of …
[HTML][HTML] Significance of machine learning in healthcare: Features, pillars and applications
Abstract Machine Learning (ML) applications are making a considerable impact on
healthcare. ML is a subtype of Artificial Intelligence (AI) technology that aims to improve the …
healthcare. ML is a subtype of Artificial Intelligence (AI) technology that aims to improve the …
Data collection and quality challenges in deep learning: A data-centric ai perspective
Data-centric AI is at the center of a fundamental shift in software engineering where machine
learning becomes the new software, powered by big data and computing infrastructure …
learning becomes the new software, powered by big data and computing infrastructure …
Secure, privacy-preserving and federated machine learning in medical imaging
GA Kaissis, MR Makowski, D Rückert… - Nature Machine …, 2020 - nature.com
The broad application of artificial intelligence techniques in medicine is currently hindered
by limited dataset availability for algorithm training and validation, due to the absence of …
by limited dataset availability for algorithm training and validation, due to the absence of …
Federated learning: A survey on enabling technologies, protocols, and applications
This paper provides a comprehensive study of Federated Learning (FL) with an emphasis
on enabling software and hardware platforms, protocols, real-life applications and use …
on enabling software and hardware platforms, protocols, real-life applications and use …
Developing future human-centered smart cities: Critical analysis of smart city security, Data management, and Ethical challenges
As the globally increasing population drives rapid urbanization in various parts of the world,
there is a great need to deliberate on the future of the cities worth living. In particular, as …
there is a great need to deliberate on the future of the cities worth living. In particular, as …
Deep learning image reconstruction for CT: technical principles and clinical prospects
Filtered back projection (FBP) has been the standard CT image reconstruction method for 4
decades. A simple, fast, and reliable technique, FBP has delivered high-quality images in …
decades. A simple, fast, and reliable technique, FBP has delivered high-quality images in …
Leveraging data science to combat COVID-19: A comprehensive review
COVID-19, an infectious disease caused by the SARS-CoV-2 virus, was declared a
pandemic by the World Health Organisation (WHO) in March 2020. By mid-August 2020 …
pandemic by the World Health Organisation (WHO) in March 2020. By mid-August 2020 …
Collaborative federated learning for healthcare: Multi-modal covid-19 diagnosis at the edge
Despite significant improvements over the last few years, cloud-based healthcare
applications continue to suffer from poor adoption due to their limitations in meeting stringent …
applications continue to suffer from poor adoption due to their limitations in meeting stringent …