Latest AI and machine learning research in diabetes for healthcare professionals.
Diabetic retinopathy (DR) is a major cause of preventable blindness, creating a need for accurate an...
Despite the growing number of public datasets, annotated medical images remain scarce. Supervised le...
Age-related macular degeneration (AMD) and diabetic macular edema (DME) are leading causes of vision...
In this work, we propose a structural variant of the Factorial Hidden Markov Model (FHMM) for the an...
Background Glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 (SGL...
Timely risk classification is essential in many clinical monitoring settings, where decisions must b...
Adverse Pregnancy Outcomes (APOs) such as preterm birth and gestational diabetes can have long-term ...
Imputing physiological time series (arterial blood pressure, blood glucose, etc.) is essential for a...
Fairness in medical imaging is commonly evaluated through subgroup performance metrics, yet it remai...
Abstract Background: Every non-invasive continuous glucose monitoring (NI-CGM) technology introduced...
Background Existing insulin resistance (IR) indices are predominantly developed in diabetic cohorts,...
Purpose: To evaluate whether fluorescence lifetime imaging ophthalmoscopy (FLIO) combined with deep ...
Metabolomics knowledge is distributed across heterogeneous resources and remains difficult to transl...
Non-invasive blood glucose level (BGL) estimation from photoplethysmography (PPG) holds great promis...
Diabetic retinopathy (DR) screening commonly relies on fixed follow-up intervals, although progressi...
Conventional subgroup analyses can yield unstable and difficult-to-interpret conclusions, especially...
Analytical technologies that can provide quick, precise, and continuous information regarding proces...
Glaucoma is a group of eye diseases that damage the optic nerve, often caused by elevated intraocula...
Deploying diabetic retinopathy (DR) screening models in primary care requires edge-efficient systems...
Clinical decisions for determining optimal patient-specific interventions are complicated prediction...
Preprocessing blood glucose time-series data is a critical yet often overlooked step in developing d...