Diabetes at IgMin Research | Medicine Group
We seek to promote cross-disciplinary innovation for quicker and more impactful outcomes.
About
Diabetes is a chronic metabolic disorder characterized by elevated blood glucose levels resulting from impaired insulin production or function. This condition poses significant global health challenges, impacting millions of individuals and contributing to complications such as cardiovascular disease, neuropathy, and kidney failure. Researchers in the field of Diabetes focus on understanding the underlying genetic, molecular, and lifestyle factors that contribute to its development, with the goal of improving prevention, diagnosis, and treatment strategies.
The study of Diabetes integrates insights from endocrinology, molecular biology, and clinical medicine to address both Type 1 and Type 2 diabetes, as well as gestational diabetes. By exploring areas such as insulin resistance, glucose metabolism, and the role of the microbiome, researchers aim to develop innovative therapies and personalized interventions. Advances in diabetes research are crucial for reducing the burden of this disease, enhancing patient outcomes, and promoting long-term health and quality of life.
Why publish with us?
Global Visibility – Indexed in major databases
Fast Peer Review – Decision within 14–21 days
Open Access – Maximize readership and citation
Multidisciplinary Scope – Biology, Medicine and Engineering
Editorial Board Excellence – Global experts involved
University Library Indexing – Via OCLC
Permanent Archiving – CrossRef DOI
APC – Affordable APCs with discounts
Citation – High Citation Potential
Which articles are now trending?
Research Articles
- Screening for Sexually Transmitted Infections in Adolescents with Genitourinary Complaints: Is There a Still Role for Endocervical Gram Stains?
- Investigation and Energy Modeling of New Generation Environmentally Friendly Energy Source Thorium Fueled Molten Salt Reactors
- Scientific Productivity of the Internet of Things (IoT) in 2011-2025: A Bibliometric Analysis
- Melanocytic Nevi Classification using Transfer Learning
- A Machine Learning-based Method for COVID-19 and Pneumonia Detection
- A Comprehensive Methodology for Assessing the Business Reputation of Industrial and Production Personnel
