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[HTML][HTML] Machine learning and smart devices for diabetes management: Systematic review
(1) Background: The use of smart devices to better manage diabetes has increased
significantly in recent years. These technologies have been introduced in order to make life …
significantly in recent years. These technologies have been introduced in order to make life …
Minimally invasive electrochemical continuous glucose monitoring sensors: Recent progress and perspective
Diabetes and its complications are seriously threatening the health and well-being of
hundreds of millions of people. Glucose levels are essential indicators of the health …
hundreds of millions of people. Glucose levels are essential indicators of the health …
Designing interpretable ML system to enhance trust in healthcare: A systematic review to proposed responsible clinician-AI-collaboration framework
Background Artificial intelligence (AI)-based medical devices and digital health
technologies, including medical sensors, wearable health trackers, telemedicine, mobile …
technologies, including medical sensors, wearable health trackers, telemedicine, mobile …
[HTML][HTML] FLIRT: A feature generation toolkit for wearable data
Abstract Background and Objective: Researchers use wearable sensing data and machine
learning (ML) models to predict various health and behavioral outcomes. However, sensor …
learning (ML) models to predict various health and behavioral outcomes. However, sensor …
[HTML][HTML] Overview of artificial intelligence–driven wearable devices for diabetes: sco** review
Background Prevalence of diabetes has steadily increased over the last few decades with
1.5 million deaths reported in 2012 alone. Traditionally, analyzing patients with diabetes has …
1.5 million deaths reported in 2012 alone. Traditionally, analyzing patients with diabetes has …
Sense and learn: recent advances in wearable sensing and machine learning for blood glucose monitoring and trend-detection
Diabetes mellitus is characterized by elevated blood glucose levels, however patients with
diabetes may also develop hypoglycemia due to treatment. There is an increasing demand …
diabetes may also develop hypoglycemia due to treatment. There is an increasing demand …
[HTML][HTML] Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data
Abstract Introduction Diabetes Mellitus (DM) is characterized by impaired ability to
metabolize glucose for use in cells for energy, resulting in high blood sugar (hyperglycemia) …
metabolize glucose for use in cells for energy, resulting in high blood sugar (hyperglycemia) …
[HTML][HTML] Type 1 diabetes hypoglycemia prediction algorithms: systematic review
Background: Diabetes is a chronic condition that necessitates regular monitoring and self-
management of the patient's blood glucose levels. People with type 1 diabetes (T1D) can …
management of the patient's blood glucose levels. People with type 1 diabetes (T1D) can …
[HTML][HTML] Physiokit: An open-source, low-cost physiological computing toolkit for single-and multi-user studies
The proliferation of physiological sensors opens new opportunities to explore interactions,
conduct experiments and evaluate the user experience with continuous monitoring of bodily …
conduct experiments and evaluate the user experience with continuous monitoring of bodily …
[HTML][HTML] A review of methods and applications for a heart rate variability analysis
Heart rate variability (HRV) has emerged as an essential non-invasive tool for
understanding cardiac autonomic function over the last few decades. This can be attributed …
understanding cardiac autonomic function over the last few decades. This can be attributed …