Alzheimers Disease at IgMin Research | Medicine Group
Our aspiration is to merge expertise across disciplines to accelerate scientific discovery.
About
Alzheimer's disease is a progressive neurodegenerative disorder that leads to cognitive decline, memory loss, and behavioral changes. It is one of the most common causes of dementia, significantly impacting individuals, families, and healthcare systems worldwide. The study of Alzheimer's focuses on understanding the underlying mechanisms of neurodegeneration, exploring factors like amyloid-beta plaques, tau tangles, and neuroinflammation. Researchers in this field are committed to discovering innovative diagnostic tools, preventive strategies, and effective therapies to slow the progression of this debilitating disease.
Advances in Alzheimer's research are crucial for addressing the growing global burden of this condition, especially in aging populations. By integrating insights from genetics, molecular biology, and neuroscience, researchers are unraveling the complex interactions that contribute to the onset and progression of Alzheimer’s. This multidisciplinary approach holds promise for developing novel interventions, improving patient care, and ultimately enhancing the quality of life for those affected by the disease.
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
- Efficacy of Alternative Insecticides against Dusky Cotton Bug (Oxycarenus laetus) to Improve Yield Losses in Cotton Crops through Residue-based Bioassay
- Improved Energy Valley Optimizer with Levy Flight for Optimization Problems
- Clustering of Three-dimensional (3-D) Objects by Means of Phase- only Digital Holographic Information using Machine Learning
- A New Modification of Classification of Traumatic Patients with Pelvic Fracture
- Comparing Forecasting Models for Predicting Infant Mortality: VECM vs. VAR and BVAR Specifications
- Benzo[4’,5’]imidazo[2’,1’:6,1]pyrido[2,3-d]pyrimidines: Past and Present
