Latest AI and machine learning research in diabetes for healthcare professionals.
Growing rates of chronic wound occurrence, especially in patients with diabetes, has become a recent concerning trend. Chronic wounds are difficult and costly to treat, and have become a serious burden on health care systems worldwide. Innovative deep learning methods for the detection and monitoring of such wounds have the potential to reduce the impact to patients and clinicians. We present a no...
This scoping review aims to identify regulator-approved ophthalmic image analysis artificial intelligence as a medical device (AIaMD) in three jurisdictions, examine their characteristics and regulatory approvals, and evaluate the available evidence underpinning them, as a step towards identifying best practice and areas for improvement. 36 AIaMDs from 28 manufacturers were identified - 97% (35/36...
Diabetes is a growing chronic disease with complications that impose a significant burden on healthcare systems worldwide. Pharmacists are readily acc...
This article analyzes the progress of animal experiments on the analgesic mechanism of electroacupuncture (EA) at the central level for neuropathic pa...
BACKGROUND: Research on the associations between the stress hyperglycemia ratio (SHR) and adverse outcomes in patients with hemorrhagic stroke is limi...
Recent advances in deep learning and machine learning have greatly increased the capabilities of extracting features for evaluating the response to an...
Our study aims to improve the prediction performance of machine learning (ML) models by addressing false records (i.e., false positive, false negative...
OBJECTIVE: Deep learning (DL) has been used to differentiate papilledema from healthy eyes and optic disc elevation on fundus photos. As we described ...
Dipeptidyl peptidase-4 (DPP-4) inhibitors play a critical role in the management of type 2 diabetes; however, some synthetic drugs may cause adverse e...
BACKGROUND: AI-assisted blood glucose management has become a promising method to enhance diabetes care, leveraging technologies like continuous gluco...
Diabetes is a prevalent chronic disease that poses a significant burden on individuals and healthcare systems. Early diagnosis and effective managemen...
The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is rapidly increasing and is caused by excessive fat deposition in ...
Accurate detection of insulin secretion from pancreatic beta cells is crucial for understanding normal physiological insulin secretion and its pathoph...
Glioblastoma multiforme is a lethal disease, with a 5-year survival rate of <10%. The identification of risk factors for glioblastoma multiforme is es...
Type 2 diabetes (T2D) is influenced by lifestyle, genetics, and environmental conditions. By utilizing machine learning techniques, we can enhance th...
The pathogenesis of diabetic cardiomyopathy (DCM) remains incompletely understood. The present study employed weighted gene co‑expression network anal...
OBJECTIVE: This study investigated EEG microstate dynamics in trigeminal neuralgia (TN) patients to understand the central nervous system's contributi...
Prediabetes represents an early stage of glucose metabolism disorder with significant public health implications. Although traditional lifestyle inter...
PURPOSE: To evaluate and quantify diabetes-related retinal and choroid perfusion changes in individuals with and without high myopia and explore their...
The association between obesity and cancer risk carries substantial public health ramifications as obesity promotes cancer advancement via many cellul...