AIMC Topic: Diabetes Mellitus, Type 1
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Personalized blood glucose prediction in type 1 diabetes using meta-learning with bidirectional long short term memory-transformer hybrid model.
Scientific reports
Aug 20, 2025
Personalized blood glucose (BG) prediction in Type 1 Diabetes (T1D) is challenged by significant inter-patient heterogeneity. To address this, we propose BiT-MAML, a hybrid model combining a Bidirectional LSTM-Transformer with Model-Agnostic Meta-Lea...
Exploration of autophagy-associated genes and potential molecular mechanisms in type 1 diabetes and osteoporosis.
Scientific reports
Aug 11, 2025
The co-occurrence of osteoporosis (OP) and type 1 diabetes mellitus (T1DM) represents a clinically significant comorbidity pattern, characterized by skeletal fragility and insulin deficiency. While epidemiological links exist, their shared molecular ...
Urinary Complement proteome strongly linked to diabetic kidney disease progression.
Nature communications
Aug 7, 2025
Diabetic kidney disease (DKD) progression is not well understood. Using high-throughput proteomics, biostatistical, pathway and machine learning tools, we examine the urinary Complement proteome in two prospective cohorts with type 1 or 2 diabetes an...
Research Gaps, Challenges, and Opportunities in Automated Insulin Delivery Systems.
Journal of diabetes science and technology
Jul 1, 2025
BACKGROUND: Since the discovery of the life-saving hormone insulin in 1921 by Dr Frederick Banting in 1921, there have been many critical discoveries and technical breakthroughs that have enabled people living with type 1 diabetes (T1D) to live longe...
Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sleeping times.
PloS one
Jun 25, 2025
Hypoglycemia is a major challenge for people with diabetes. Therefore, glycemic monitoring is an important aspect of diabetes management. However, current methods such as finger pricking and continuous glucose monitoring systems (CGMS) are invasive, ...
Intervention through an intelligent technological platform for socio-emotional development and health promotion in adolescents with Type 1 Diabetes Mellitus (emoTICare): A study protocol for randomized controlled trial.
PloS one
Jun 23, 2025
BACKGROUND: During adolescence, individuals face various challenges that require adequate psychosocial and emotional adjustment. Additionally, the presence of a chronic illness during this stage, such as Type 1 Diabetes Mellitus (T1DM), introduces ad...
Insulin resistance in type 1 diabetes is a key modulator of platelet hyperreactivity.
Diabetologia
Apr 30, 2025
AIMS/HYPOTHESIS: Individuals with type 1 diabetes are at increased cardiovascular risk, particularly in the presence of insulin resistance. A prothrombotic environment is believed to contribute to this risk but thrombotic pathways in type 1 diabetes ...
Modeling the number of new cases of childhood type 1 diabetes using Poisson regression and machine learning methods; a case study in Saudi Arabia.
PloS one
Apr 25, 2025
Diabetes mellitus stands out as one of the most prevalent chronic conditions affecting pediatric populations. The escalating incidence of childhood type 1 diabetes (T1D) globally is a matter of increasing concern. Developing an effective model that l...
Personalized glucose forecasting for people with type 1 diabetes using large language models.
Computer methods and programs in biomedicine
Apr 2, 2025
BACKGROUND AND OBJECTIVE: Type 1 Diabetes (T1D) is an autoimmune disease that requires exogenous insulin via Multiple Daily Injections (MDIs) or subcutaneous pumps to maintain targeted glucose levels. Despite the advances in Continuous Glucose Monito...
Personalized Blood Glucose Forecasting From Limited CGM Data Using Incrementally Retrained LSTM.
IEEE transactions on bio-medical engineering
Mar 21, 2025
For people with Type 1 diabetes (T1D), accurate blood glucose (BG) forecasting is crucial for the effective delivery of insulin by Artificial Pancreas (AP) systems. Deep learning frameworks like Long Short-Term-Memory (LSTM) have been widely used to ...
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