Latest AI and machine learning research in endocrinology for healthcare professionals.
Background: Although diabetes is a potent risk factor for the development of peripheral artery disease (PAD), the effect of cumulative metabolic exposure to hyperglycemia on risk of cardiovascular or limb events in patients with PAD remains unclear. Methods: The Peripheral Artery Disease: Long-term Survival (PEARLS) is a longitudinal registry of Veterans with newly diagnosed PAD identified using a...
Purpose: To investigate how artificial intelligence (AI) systems detect referrable diabetic retinopathy (DR) from retinal photographs by analysing heatmap patterns and determining their overlap with DR features. Methods: Fifty-four AI systems were developed using 27 backbone architectures, with each implemented as both binary-referable and multi-class grading models based on the International Clin...
Background Anthropometric measures do not adequately capture heterogeneity in body fat distribution and corresponding cardiometabolic risk, whereas ma...
Offline reinforcement learning (ORL) offers the potential to improve the quality of clinical decision-making using historical electronic health record...
Pharmacological interventions targeting the biological processes of ageing hold significant potential to extend healthspan and promote longevity. This...
Glucose forecasting algorithms are an important aspect of glycemic control management in type 1 diabetes. So far, the research community has developed...
Chronic disease management relies on regular patient-provider interactions to follow-up on disease progression and control. For Type 2 Diabetes (T2D),...
Dysglycemia, encompassing both prediabetes and diabetes, affects huge numbers of adults worldwide, yet many of them remain undiagnosed. We developed a...
Patients diagnosed with type 2 diabetes (T2D) are at increased risk of developing cardiovascular disease (CVD), the leading cause of morbidity and mor...
Introduction: Precise anatomical navigation is fundamental to safe endoscopic pituitary surgery, a high-stakes procedure characterised by a challengin...
Type 2 Diabetes (T2D) poses an increasing global health threat, demanding effective glycemic assessment to support personalized and improved diabetes ...
Background. Type 2 diabetes mellitus (T2D) is defined by progressive pancreatic {beta}-cell dysfunction whose molecular underpinnings remain incomplet...
Background The European Association for the Study of the Liver (ESAL) - Steatotic Liver Disease (SLD) screening algorithm involves two steps; initial ...
Circulating-tumour DNA (ctDNA) carries evidence of drug resistance months before imaging shows it, but the earliest evidence lives below the assay's l...
Clinicians diagnose brain tumors by synthesizing patient symptoms, medical history, and quantitative imaging data from modalities such as MRI and CT s...
Background: This study aimed to evaluate real-world adverse event (AE) signals of EV to provide evidence-based guidance for its safe clinical applicat...
Human pancreatic islets exhibit greater anatomic and cellular heterogeneity than previously appreciated, raising fundamental questions about how their...
Clinicians diagnose brain tumors by synthesizing patient symptoms, medical history, and quantitative imaging data from modalities such as MRI and CT s...
Postprandial hyperglycemia is a key risk factor for metabolic disorders; however, existing dietary guidance is often static, impractical, and insuffic...
Background Machine learning (ML) models are increasingly used to predict adverse outcomes after surgery. However, most rely on static patient characte...