Latest AI and machine learning research in diabetes for healthcare professionals.
The second track of the 2014 i2b2/UTHealth natural language processing shared task focused on identi...
To provide an overview of the anatomical landmarks needed to guide a retropubic (Retzius)-sparing ro...
An alternative bioinformatics approach based on fuzzy theory statistics and linear discriminant anal...
Heart disease is the leading cause of death globally and a significant part of the human population ...
Prolonged diabetes retinopathy leads to diabetes maculopathy, which causes gradual and irreversible ...
AIMS/INTRODUCTION: The changes in metabolic parameters in type 2 diabetic patients who fast during R...
BACKGROUND AND OBJECTIVE: Understanding the causes of disagreement among experts in clinical decisio...
BACKGROUND: Preoperative type 2 diabetes mellitus (T2 DM) has previously been reported as an indepen...
The present work presents the comparative assessment of four glucose prediction models for patients ...
AIMS/INTRODUCTION: Anemia has a close interaction with renal dysfunction in diabetes patients. More ...
The 2014 i2b2/UTHealth natural language processing shared task featured a track focused on identifyi...
Among the many related issues of diabetes management, its complications constitute the main part of ...
There has recently been much advancement in the diagnosis, treatment, and research of metabolic diso...
Systemic erythematosus lupus (SLE) is a multisystemic autoimmune disease which has nephritis as one ...
OBJECTIVE: To investigate the effects of general anaesthesia and general+epidural anaesthesia on the...
The hypertriglyceridemic waist (HW) phenotype is strongly associated with type 2 diabetes; however, ...
The purpose of this study was to quantify associations between hemoglobin A1C (A1C) and diabetes kno...
In this paper, a non-invasive blood glucose sensing system is presented using near infra-red(NIR) sp...
OBJECTIVE: To evaluate the impact of the synthetic minority oversampling technique (SMOTE) on the pe...
OBJECTIVE: Inter-expert variability in image-based clinical diagnosis has been demonstrated in many ...
Supervised machine learning is a powerful tool frequently used in computer-aided diagnosis (CAD) app...