Latest AI and machine learning research in diabetes for healthcare professionals.
OBJECTIVE: Precise mealtime insulin bolus (MIB) dosing is essential in type 1 diabetes (T1D) to minimize glucose excursions from carbohydrate intake. Traditional MIB formulas, based on glucose concentration at mealtime, are suboptimal and do not exploit real-time data from continuous glucose monitoring (CGM). Existing methods that incorporate CGM data often rely on empirical rules or are developed...
BACKGROUND: Lung cancer is a leading cause of cancer-related mortality, and its prognosis is often affected by comorbidities such as type 2 diabetes mellitus (T2DM). This study aimed to identify survival risk factors for lung cancer patients with T2DM, evaluate the predictive models, and develop a risk score system for survival prediction. STUDY DESIGN AND METHODS: We analyzed data from 5491 lung ...
BACKGROUND: Family history of pancreatic cancer (PC), pathogenic germline variants (PGVs), and increased intrapancreatic fat (IPF) are individually as...
Noninvasive wearable sweat sensors are promising for personalized health management, yet their widespread adoption is hindered by complex multi-compon...
Smartphone-based fundus imaging (SBFI) is an emerging approach with potential relevance for global ophthalmic care, including in low- and middle-incom...
BACKGROUND: Diabetes has reached epidemic proportions in Pakistan. This study applied machine learning (ML) techniques to identify comorbidity-based a...
INTRODUCTION: Diabetes affects 537 million people worldwide, with type 2 diabetes (T2D) estimated to account for most cases. Type 1 diabetes (T1D), la...
BACKGROUND: Gestational diabetes mellitus (GDM) affects 1-in-7 pregnancies globally and is associated with significant short- and long-term health con...
OBJECTIVES: Acute pancreatitis (AP) carries a high mortality risk in ICU patients. The glucose-to-albumin ratio (GAR), reflecting metabolic stress and...
BACKGROUND: Deep-learning models are capable of predicting age from retinal scans and the difference between this and chronological age, retinal age g...
BACKGROUND & AIMS: Noninvasive tests to identify pediatric metabolic dysfunction-associated steatohepatitis (MASH) remain a critical need. We aimed to...
Precision medicine has revolutionized oncology by leveraging biomarkers for individualized therapy selection, early diagnosis, and real-time disease m...
BACKGROUND: Body mass index fails to capture variation in fat and muscle distribution that determines metabolic health and disease risk. MRI enables r...
OBJECTIVE: Independent of clinical risk factors, performing well-day capillary ketone monitoring over a month predicts near-term diabetic ketoacidosis...
INTRODUCTION: Chronic kidney disease (CKD) disproportionately burdens non-Hispanic Black (NHB) patients who experience a three- to four-fold higher ri...
BACKGROUND: RETFound, a self-supervised retina-specific foundation model, has shown potential in downstream tasks, but its performance in comparison w...
BACKGROUND: The triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio and triglyceride glucose-body mass (TyG-BMI) index are reliable ...
Protein Tyrosine Phosphatases (PTPs) regulate cellular signaling by balancing phosphotyrosine levels through a conserved WPD-loop that switches betwee...
Traditional systems of ocular disease diagnosis and many deep learning-based systems are limited in their practice to analyzing fundus images from a s...
BACKGROUND: Machine learning (ML) has emerged as a promising tool for predicting diabetic kidney disease (DKD), yet the performance and clinical utili...