Addiction Medicine at IgMin Research | Medicine Group
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About
Addiction Medicine is a multidisciplinary field that addresses the complex nature of addiction, integrating approaches from psychiatry, neuroscience, and pharmacology. This dynamic discipline explores the mechanisms underlying substance use disorders and behavioral addictions, with a focus on prevention, diagnosis, treatment, and recovery. Researchers in Addiction Medicine aim to understand the biological, psychological, and social factors that contribute to addictive behaviors, developing innovative strategies to support individuals in overcoming addiction.
By leveraging insights from genetics, neurobiology, and behavioral sciences, the study of Addiction Medicine is pivotal in advancing therapies for substance dependence and addictive behaviors. The field also encompasses research on comorbid mental health conditions, harm reduction, and evidence-based interventions that enhance patient outcomes. As addiction continues to pose significant public health challenges worldwide, the advancements in this field are crucial for improving treatment options and promoting long-term recovery.
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
- The Influence of Dynamical Downscaling and Boundary Layer Selection on Egypt’s Potential Evapotranspiration using a Calibrated Version of the Hargreaves-samani Equation: RegCM4 Approach
- A Machine Learning-based Method for COVID-19 and Pneumonia Detection
- Challenge and Readiness to Implemented Geothermal Energy in Indonesia
- Enhancing Material Property Predictions through Optimized KNN Imputation and Deep Neural Network Modeling
- Prevalence of Non-specific Low Back Pain Among Chinese Healthcare Workers (Surgeons and Surgical Nurses): A Multi-Center Survey Study
- A Unified Mobility Model for Semiconductor Devices and Sensors, Including Surface Hydrodynamic Viscosity
