Hepatology at IgMin Research | Medicine Group
We seek to promote interdisciplinary learning and growth to accelerate the pace of innovation.
About
Hepatology is the branch of medicine focused on the study, diagnosis, and treatment of liver, gallbladder, biliary tree, and pancreatic disorders. This field addresses critical conditions such as hepatitis, cirrhosis, fatty liver disease, and liver cancer, which pose significant health challenges worldwide. Researchers in Hepatology aim to understand the complex mechanisms underlying liver function, injury, and repair, leading to advancements in therapeutic interventions and liver transplantation.
The study of Hepatology integrates insights from molecular biology, immunology, and clinical medicine to improve the diagnosis and management of liver diseases. By exploring areas such as viral hepatitis, liver fibrosis, and non-alcoholic fatty liver disease, research in hepatology is essential for developing novel therapies and enhancing patient outcomes. Advancements in this field are crucial for reducing the burden of liver-related diseases and improving liver health globally.
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
- Cyber Threat Analysis (CTA) in Current Conflicts
- Gaussian-Transform for the Dirac Wave Function and its Application to the Multicenter Molecular Integral Over Dirac Wave Functions for Solving the Molecular Matrix Dirac Equation
- Synergistic Assessment of Supplementation of Ascorbic Acid and Massularia acuminata Extracts on Serum Electrolyte and Lipid Profile Indices of Dyslipidemia in Adult Wistar Rats Exposed to Aluminum Chloride Toxicity
- Enhancing Material Property Predictions through Optimized KNN Imputation and Deep Neural Network Modeling
- The Influence of Low Pesticide Doses on Fusarium Molds
- Modeling of Cr3+ doped Cassiterite (SnO2) Single Crystals
