Related papers: Patterns Detection in Glucose Time Series by Domai…
Genome-Wide Association Studies are typically conducted using linear models to find genetic variants associated with common diseases. In these studies, association testing is done on a variant-by-variant basis, possibly missing out on…
Deep Learning (DL) models can be used to tackle time series analysis tasks with great success. However, the performance of DL models can degenerate rapidly if the data are not appropriately normalized. This issue is even more apparent when…
Time series data, defined by equally spaced points over time, is essential in fields like medicine, telecommunications, and energy. Analyzing it involves tasks such as classification, clustering, prototyping, and regression. Classification…
Continuous Blood Glucose (CGM) monitors have revolutionized the ability of diabetics to manage their blood glucose, and paved the way for artificial pancreas systems. In this paper we augment CGM data with sensor input collected by a smart…
Diabetes is a chronic metabolic disorder characterized by persistently high blood glucose levels (BGLs), leading to severe complications such as cardiovascular disease, neuropathy, and retinopathy. Predicting BGLs enables patients to…
This paper presents the Derivatives Combination Predictor (DCP), a novel model fusion algorithm for making long-term glucose predictions for diabetic people. First, using the history of glucose predictions made by several models, the future…
A composite, exponential relaxation function, modulated by a periodic component, was used to fit to an experimental time series of blood glucose levels. The 11 parameters function that allows for the detection of a possible rhythm…
In the UK, approximately 400,000 people with type 1 diabetes (T1D) rely on insulin delivery due to insufficient pancreatic insulin production. Managing blood glucose (BG) levels is crucial, with continuous glucose monitoring (CGM) playing a…
Background: Predictive modeling is a key component of solutions to many healthcare problems. Among all predictive modeling approaches, machine learning methods often achieve the highest prediction accuracy, but suffer from a long-standing…
Diabetes mellitus is a global concern, and early detection can prevent serious complications. 50% of people with diabetes live undiagnosed, disproportionately afflicting low-income groups. Non-invasive methods have emerged for timely…
Diabetes is a prevalent chronic disease with significant health and economic burdens worldwide. Early prediction and diagnosis can aid in effective management and prevention of complications. This study explores the use of machine learning…
An algorithm based on PLS regression has been developed and optimized for measuring blood glucose level using the infra-red transmission spectrum of blood samples. A set of blood samples were tagged with their glucose concentration using an…
The Transformer is a highly successful deep learning model that has revolutionised the world of artificial neural networks, first in natural language processing and later in computer vision. This model is based on the attention mechanism…
Early diagnosis of treatable diseases is essential for improving healthcare, and many diseases' onsets are predictable from annual lab tests and their temporal trends. We introduce a multi-resolution convolutional neural network for early…
Widespread outreach programs using remote retinal imaging have proven to decrease the risk from diabetic retinopathy, the leading cause of blindness in the US. However, this process still requires manual verification of image quality and…
Type 2 Diabetes is one of the most major and fatal diseases known to human beings, where thousands of people are subjected to the onset of Type 2 Diabetes every year. However, the diagnosis and prevention of Type 2 Diabetes are relatively…
The purpose of this Conference is to present the main lines of base projects that are founded on research already begun in previous years. In this sense, this manuscript will present the main lines of research in Diabetes Mellitus type 1…
As witnessed in the past year, where the world was brought to the ground by a pandemic, fighting Life-threatening diseases have found greater focus than ever. The first step in fighting a disease is to diagnose it at the right time.…
In many nations, diabetes is becoming a significant health problem, and early identification and control are crucial. Using machine learning algorithms to predict diabetes has yielded encouraging results. Using the Pima Indians Diabetes…
Diabetic Retinopathy (DR) is a serious and common complication of diabetes, caused by prolonged high blood sugar levels that damage the small retinal blood vessels. If left untreated, DR can progress to retinal vein occlusion and stimulate…