Track: Innovations in Diabetes Diagnosis

Traditional and Emerging Biomarkers for Early Detection: Key biomarkers, like insulin and C-peptide, alongside novel markers, help identify diabetes risk and progression at earlier stages.
Continuous Glucose Monitoring and its Advancements: Real-time glucose tracking devices have evolved with better accuracy, non-invasive methods, and AI-driven insights.
HbA1c and Other Diagnostic Criteria: HbA1c, fasting glucose, and oral glucose tolerance tests remain primary methods for diagnosing and monitoring diabetes.
Role of Genetic Testing in Diabetes Risk Prediction: Genetic testing identifies predisposition to diabetes, enabling personalized prevention and treatment strategies.
The Future of AI in Diabetes Diagnostics: AI enhances diabetes prediction, personalized care, and decision-making through big data analysis and machine learning.
Ethical Considerations and Data Privacy in Diabetes Diagnosis: Exploring the ethical challenges surrounding the use of AI and big data in diabetes diagnosis, including patient privacy, consent, and the potential for algorithmic bias.
Scientific Highlights
- Understanding Diabetes: Pathophysiology and Mechanisms
- Innovations in Diabetes Diagnosis
- Diabetes and Cardiovascular Health
- Endocrine Disorders: Overview and Classification
- Diabetes Management: Pharmacological Approaches
- Lifestyle Modifications in Managing Diabetes and Endocrine Disorders
- Pediatric Endocrinology and Diabetes
- Future Directions in Diabetes and Endocrinology
- Thyroid Disorders, Diabetes and Women’s Health : A Complex Relationship
- Next Generation Diabetology
- Fertility and Endocrine Disorders
- Point of View: Upcoming Trends and Innovations in Diabetes Diagnosis and Treatment
- Diabetes-Neuropathy
- Emerging Research in Endocrinology and Metabolic Health
- Neuroendocrinology and Brain-Body Interactions
- Artificial Intelligence and Data Analytics in Diabetes Care