Medical & biological engineering & computing
Jun 7, 2015
The present work presents the comparative assessment of four glucose prediction models for patients with type 1 diabetes mellitus (T1DM) using data from sensors monitoring blood glucose concentration. The four models are based on a feedforward neural...
Families, systems & health : the journal of collaborative family healthcare
Jan 19, 2015
The purpose of this study was to quantify associations between hemoglobin A1C (A1C) and diabetes knowledge score using an assessment tool developed to evaluate the level of diabetes knowledge in young adults with Type 1 diabetes (T1DM) and their pare...
In this paper, a non-invasive blood glucose sensing system is presented using near infra-red(NIR) spectroscopy. The signal from the NIR optodes is processed using artificial neural networks (ANN) to estimate the glucose level in blood. In order to ob...
The Journal of clinical endocrinology and metabolism
Apr 22, 2025
CONTEXT: Large-for-gestational-age (LGA), one of the most common complications of gestational diabetes mellitus (GDM), has become a global concern. The predictive performance of common continuous glucose monitoring (CGM) metrics for LGA is limited.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2025
BACKGROUND: Machine learning offers diverse options for effectively managing blood glucose levels in diabetes patients. Selecting the right ML algorithm is critical given the array of available choices. Integrating data from IoT devices presents prom...
BACKGROUND: Diabetes Mellitus is a chronic health condition (long-lasting) due to inadequate control of blood levels of glucose. This study presents a prediction of Type 2 Diabetes Mellitus among women using various Machine Learning Algorithms deploy...
OBJECTIVE: Individuals living with obesity are differentially susceptible to cardiometabolic diseases. We hypothesized that an integrative multi-omics approach might improve identification of subgroups of individuals with obesity who have distinct ca...
Diabetes/metabolism research and reviews
Nov 1, 2024
BACKGROUND: Prediabetes and diabetes are both abnormal states of glucose metabolism (AGM) that can lead to severe complications. Early detection of AGM is crucial for timely intervention and treatment. However, fasting blood glucose (FBG) as a mass p...
Studies in health technology and informatics
Aug 22, 2024
This study developed and validated a machine learning model for predicting glycemic control in children with type 1 diabetes at the time of diagnosis, revealing age at diagnosis as the most informative predictor.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
In the U.S., over a third of adults are pre-diabetic, with 80% unaware of their status. This underlines the need for better glucose monitoring to prevent type 2 diabetes and related heart diseases. Existing wearable glucose monitors are limited by th...