End-to-end design of wearable sensors
Wearable devices provide an alternative pathway to clinical diagnostics by exploiting
various physical, chemical and biological sensors to mine physiological (biophysical and/or …
various physical, chemical and biological sensors to mine physiological (biophysical and/or …
Wearable chemical sensors for biomarker discovery in the omics era
JR Sempionatto, JA Lasalde-Ramírez… - Nature Reviews …, 2022 - nature.com
Biomarkers are crucial biological indicators in medical diagnostics and therapy. However,
the process of biomarker discovery and validation is hindered by a lack of standardized …
the process of biomarker discovery and validation is hindered by a lack of standardized …
Predicting the onset of diabetes with machine learning methods
CY Chou, DY Hsu, CH Chou - Journal of Personalized Medicine, 2023 - mdpi.com
The number of people suffering from diabetes in Taiwan has continued to rise in recent
years. According to the statistics of the International Diabetes Federation, about 537 million …
years. According to the statistics of the International Diabetes Federation, about 537 million …
[HTML][HTML] Mobile and wearable technology for the monitoring of diabetes-related parameters: Systematic review
C Rodriguez-León, C Villalonga… - JMIR mHealth and …, 2021 - mhealth.jmir.org
Background Diabetes mellitus is a metabolic disorder that affects hundreds of millions of
people worldwide and causes several million deaths every year. Such a dramatic scenario …
people worldwide and causes several million deaths every year. Such a dramatic scenario …
Applications of artificial intelligence, machine learning, big data and the internet of things to the COVID-19 pandemic: A scientometric review using text mining
I Rodriguez-Rodriguez, JV Rodriguez… - International Journal of …, 2021 - mdpi.com
The COVID-19 pandemic has wreaked havoc in every country in the world, with serious
health-related, economic, and social consequences. Since its outbreak in March 2020, many …
health-related, economic, and social consequences. Since its outbreak in March 2020, many …
Machine learning techniques for hypoglycemia prediction: trends and challenges
(1) Background: the use of machine learning techniques for the purpose of anticipating
hypoglycemia has increased considerably in the past few years. Hypoglycemia is the drop in …
hypoglycemia has increased considerably in the past few years. Hypoglycemia is the drop in …
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 …
Forecasting of glucose levels and hypoglycemic events: head-to-head comparison of linear and nonlinear data-driven algorithms based on continuous glucose …
In type 1 diabetes management, the availability of algorithms capable of accurately
forecasting future blood glucose (BG) concentrations and hypoglycemic episodes could …
forecasting future blood glucose (BG) concentrations and hypoglycemic episodes could …
Systematic review on machine-learning algorithms used in wearable-based eHealth data analysis
In this digitized world, data has become an integral part in any domain, including healthcare.
The healthcare industry produces a huge amount of digital data, by utilizing information from …
The healthcare industry produces a huge amount of digital data, by utilizing information from …
Long-term prediction of blood glucose levels in type 1 diabetes using a cnn-lstm-based deep neural network
Background: In this work, we leverage state-of-the-art deep learning–based algorithms for
blood glucose (BG) forecasting in people with type 1 diabetes. Methods: We propose stacks …
blood glucose (BG) forecasting in people with type 1 diabetes. Methods: We propose stacks …