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 …
[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 …
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] Overview of artificial intelligence–driven wearable devices for diabetes: scoping 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 …
[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) …
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 …
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] Type 1 diabetes hypoglycemia prediction algorithms: systematic review
S Tsichlaki, L Koumakis, M Tsiknakis - JMIR diabetes, 2022 - diabetes.jmir.org
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 …
Development and validation of an explainable machine learning model for major complications after cytoreductive surgery
Importance Cytoreductive surgery (CRS) is one of the most complex operations in surgical
oncology with significant morbidity, and improved risk prediction tools are critically needed …
oncology with significant morbidity, and improved risk prediction tools are critically needed …