[HTML][HTML] Artificial intelligence for diabetes management and decision support: literature review
I Contreras, J Vehi - Journal of medical Internet research, 2018 - jmir.org
Background Artificial intelligence methods in combination with the latest technologies,
including medical devices, mobile computing, and sensor technologies, have the potential to …
including medical devices, mobile computing, and sensor technologies, have the potential to …
A megatrend challenging analytical chemistry: biosensor and chemosensor concepts ready for the internet of things
M Mayer, AJ Baeumner - Chemical reviews, 2019 - ACS Publications
The Internet of Things (IoT) is a megatrend that cuts across all scientific and engineering
disciplines and establishes an integrating technical evolution to improve production …
disciplines and establishes an integrating technical evolution to improve production …
Convolutional recurrent neural networks for glucose prediction
Control of blood glucose is essential for diabetes management. Current digital therapeutic
approaches for subjects with type 1 diabetes mellitus such as the artificial pancreas and …
approaches for subjects with type 1 diabetes mellitus such as the artificial pancreas and …
5G-smart diabetes: Toward personalized diabetes diagnosis with healthcare big data clouds
Recent advances in wireless networking and big data technologies, such as 5G networks,
medical big data analytics, and the Internet of Things, along with recent developments in …
medical big data analytics, and the Internet of Things, along with recent developments in …
GluNet: A deep learning framework for accurate glucose forecasting
For people with Type 1 diabetes (T1D), forecasting of blood glucose (BG) can be used to
effectively avoid hyperglycemia, hypoglycemia and associated complications. The latest …
effectively avoid hyperglycemia, hypoglycemia and associated complications. The latest …
Advanced diabetes management using artificial intelligence and continuous glucose monitoring sensors
Wearable continuous glucose monitoring (CGM) sensors are revolutionizing the treatment of
type 1 diabetes (T1D). These sensors provide in real-time, every 1–5 min, the current blood …
type 1 diabetes (T1D). These sensors provide in real-time, every 1–5 min, the current blood …
Dilated recurrent neural networks for glucose forecasting in type 1 diabetes
Diabetes is a chronic disease affecting 415 million people worldwide. People with type 1
diabetes mellitus (T1DM) need to self-administer insulin to maintain blood glucose (BG) …
diabetes mellitus (T1DM) need to self-administer insulin to maintain blood glucose (BG) …
A review of recurrent neural network-based methods in computational physiology
Artificial intelligence and machine learning techniques have progressed dramatically and
become powerful tools required to solve complicated tasks, such as computer vision, speech …
become powerful tools required to solve complicated tasks, such as computer vision, speech …
An insulin bolus advisor for type 1 diabetes using deep reinforcement learning
(1) Background: People living with type 1 diabetes (T1D) require self-management to
maintain blood glucose (BG) levels in a therapeutic range through the delivery of exogenous …
maintain blood glucose (BG) levels in a therapeutic range through the delivery of exogenous …
A digital ecosystem of diabetes data and technology: services, systems, and tools enabled by wearables, sensors, and apps
ND Heintzman - Journal of diabetes science and technology, 2016 - journals.sagepub.com
The management of type 1 diabetes (T1D) ideally involves regimented measurement of
various health signals; constant interpretation of diverse kinds of data; and consistent …
various health signals; constant interpretation of diverse kinds of data; and consistent …