Diabetes

Evaluation of Differential Diagnosis of Odontogenic Lesions in Cone Beam Computed Tomography Images Using Radiomics-Based Machine Learning.

OBJECTIVE: This study aimed to evaluate the structural characteristics of mandibular alveolar bone in patients with Type 1 diabetes mellitus (T1DM), Type 2 diabetes mellitus (T2DM), and systemically healthy controls using panoramic radiography-based radiomic analysis combined with machine learning algorithms. MATERIALS AND METHODS: A total of 225 panoramic radiographs (75 T1DM, 75 T2DM, 75 healthy...

A Perovskite Memdiode-Based Neuromorphic in Silico Surrogate Model for Emulating Predictive Coding Failure in Diabetic Neuropathy.

Halide perovskite memdiodes have coupled ionic-electronic dynamics and are promising candidates for artificial synapses in neuromorphic computing. We provide an in silico neuromorphic circuit that includes a comprehensive perovskite memdiode model and confirm its synaptic plasticity repertoire through simulation-based validation. The proposed model recapitulates analog long-term potentiation/depre...

Applications of artificial intelligence in rural ophthalmology: a scoping review.

OBJECTIVE: Artificial intelligence (AI) is increasingly utilized for screening within ophthalmology, yet its application in rural communities remains ...

Exploring and validating hub genes associated with atopic dermatitis through weighted gene co-expression network analysis and machine learning.

This study aimed to identify novel biomarkers of atopic dermatitis (AD) and investigate their pathogenic mechanisms. We analyzed 7 AD-related datasets...

Artificial intelligence in diabetic retinopathy: from automated screening to risk-stratified care.

Diabetic retinopathy (DR) is a leading cause of preventable blindness worldwide. The rising prevalence of diabetes has strained conventional screening...

Emerging Research Trends in the Application of Artificial Intelligence, LLMs, Machine Learning, and Deep Learning in Ophthalmic Diseases: A Bibliometric and Visual Analysis.

BACKGROUND: To examine global research activity in the application of artificial intelligence, large language models, machine learning, and deep learn...

Oxygen management and targeted methods to Attack Retinopathy of Prematurity (ROP): Progress and Possibilities.

Retinopathy of prematurity (ROP) is an eye disease that severely impacts premature infants, especially those born before 31 weeks gestation and those ...

Multimodal Deep Learning for Diabetic Retinopathy: A Survey.

Diabetic retinopathy (DR) remains a leading cause of blindness globally, driving the rapid development of automated diagnostic systems leveraging deep...

The Eye as a Window to Cardio-Kidney-Metabolic Disease.

The Cardiovascular-Kidney-Metabolic (CKM) syndrome reframes cardiovascular, kidney, and metabolic disease as an integrated continuum, yet its manageme...

Hydrogen sulfide ameliorates cognitive dysfunction in diabetic encephalopathy by activating PI3K/AKT/GSK-3β signaling to attenuate tau hyperphosphorylation and necroptosis.

Diabetic encephalopathy (DE) is a serious complication of diabetes mellitus characterized by progressive cognitive dysfunction; but its underlying mec...

Artificial Intelligence Analysis of Standard 12-Lead Electrocardiograms for Screening of Symptomatic Diabetic Peripheral Neuropathy.

AIM: To investigate whether artificial intelligence (AI) models trained on standard 12-lead electrocardiograms (ECG) can identify symptom-defined diab...

Artificial intelligence-enhanced management system for secondary prevention of coronary heart disease: a randomized clinical trial.

BACKGROUND: Secondary prevention of coronary heart disease (CHD) remains suboptimal due to fragmented care and therapeutic inertia. While digital heal...

Prospective Detection of Hypoglycemia and Near-Hypoglycemia Inducing Pressure-Induced Sensor Attenuation Onset in Continuous Glucose Monitoring Time Series.

BACKGROUND: Continuous glucose monitoring (CGM) sensors are vulnerable to pressure-induced sensor attenuations (PISAs). Pressure-induced sensor attenu...

Artificial intelligence in food and nutrition science: a paradigm-centric review of computational frameworks and system-level integration.

Precision nutrition on a global scale necessitates an understanding of food not as static collections of so-called macronutrients but rather as dynami...

Subtyping and Prediction of the Glucose Based on the Hybrid Modeling of Deep Learning and Dietary Stimulated Glucose Metabolism Dynamical Model.

Diabetes represents a significant global health challenge, underscoring the need for enhanced methodologies in glycemic monitoring and risk assessment...

Linking Metabolic Subgroups and Adverse Pregnancy Outcomes in GDM: A Complementary Analytic Approach of Logistic Regressions and Machine Learning.

AIMS: Associations between metabolic heterogeneity in women with gestational diabetes mellitus (GDM) and adverse pregnancy outcomes have often been ex...

A comprehensive review on automated diabetic retinopathy detection and classification using fundus image.

PURPOSE: Diabetic Retinopathy (DR) is a vision-threatening complication in diabetic patients. It harms retinal vessels and may lead to blindness. Dete...

Federated learning for MRI-based BrainAGE: A multicenter study on post-stroke functional outcome prediction.

OBJECTIVE: Brain-predicted age difference (BrainAGE) is a neuroimaging biomarker reflecting brain health, with potential implications for post-stroke ...

Integrative Proteomics-Metabolomics Profiling of Umbilical Cord Plasma With Machine Learning Reveals Candidate Biomarkers for Gestational Diabetes Mellitus.

BACKGROUND: Gestational diabetes mellitus (GDM) is a common pregnancy complication, yet its molecular mechanisms remain incompletely understood. This ...

Automated detection of proliferative & non-proliferative diabetic retinopathy using near-infrared and OCT imaging.

PURPOSE: Diabetic retinopathy, a major cause of blindness in working-age individuals, advances without adequate recognition and treatment from non-pro...