[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 …
[HTML][HTML] AI augmented Edge and Fog computing: Trends and challenges
In recent years, the landscape of computing paradigms has witnessed a gradual yet
remarkable shift from monolithic computing to distributed and decentralized paradigms such …
remarkable shift from monolithic computing to distributed and decentralized paradigms such …
[HTML][HTML] The pipeline for the continuous development of artificial intelligence models—Current state of research and practice
Companies struggle to continuously develop and deploy Artificial Intelligence (AI) models to
complex production systems due to AI characteristics while assuring quality. To ease the …
complex production systems due to AI characteristics while assuring quality. To ease the …
Machine learning to empower electrohydrodynamic processing
Electrohydrodynamic (EHD) processes are promising healthcare fabrication technologies,
as evidenced by the number of commercialised and food-and-drug administration (FDA) …
as evidenced by the number of commercialised and food-and-drug administration (FDA) …
The emergence of anti-privacy and control at the nexus between the concepts of safe city and smart city
Z Allam - Smart Cities, 2019 - mdpi.com
The emergence of Big Data, accelerated through the Internet of Things (IoT) and Artificial
Intelligence, from the emerging, contemporary concept of smart cities coupled with that of the …
Intelligence, from the emerging, contemporary concept of smart cities coupled with that of the …
[HTML][HTML] Algorithm-enabled, personalized glucose management for type 1 diabetes at the population scale: Prospective evaluation in clinical practice
Background: The use of continuous glucose monitors (CGMs) is recommended as the
standard of care by the American Diabetes Association for individuals with type 1 diabetes …
standard of care by the American Diabetes Association for individuals with type 1 diabetes …
Methodologies for designing healthcare analytics solutions: A literature analysis
Healthcare analytics has been a rapidly emerging research domain in recent years. In
general, healthcare solution design studies focus on developing analytic solutions that …
general, healthcare solution design studies focus on developing analytic solutions that …
From a data science driven process to a continuous delivery process for machine learning systems
Abstract Development of machine learning (ML) enabled applications in real-world settings
is challenging and requires the consideration of sound software engineering (SE) principles …
is challenging and requires the consideration of sound software engineering (SE) principles …
A new technology-enabled care model for pediatric type 1 diabetes
In July 2018, pediatric type 1 diabetes (T1D) care at Stanford suffered many of the problems
that plague US health care. Patient outcomes lagged behind those of peer European …
that plague US health care. Patient outcomes lagged behind those of peer European …
The state of the art of using artificial intelligence for disease identification and diagnosis in healthcare
I El Mir, S El Kafhali - Deep Learning for Healthcare Decision …, 2023 - taylorfrancis.com
Healthcare is a multidisciplinary term, which refers to a system that involves the
development of health services to satisfy people's medical needs. Over the past years …
development of health services to satisfy people's medical needs. Over the past years …