Medinformatics (MEDIN) is an engaging and peer-reviewed journal that serves as a platform for sharing cutting-edge research in the interdisciplinary field of biomedicine and informatics. By doing so, we aim to establish effective channels of communication and promote interdisciplinary integration between biomedicine, mathematics, and computer science.

The journal welcomes submissions fostering collaboration and innovation among medical scientists, clinicians, mathematicians, statisticians, and computer scientists.

We welcome submissions on a wide range of topics, including, but not limited to:

• Application of Machine Learning and Artificial Intelligence in Biomedicine: Explore the utilization of cutting-edge technologies in the realm of biomedicine, leveraging machine learning and artificial intelligence to unravel complex patterns and improve healthcare outcomes.

• Biomedical Data Mining and Processing: Investigate methodologies and techniques for extracting valuable insights from large-scale biomedical datasets, enabling informed decision-making and advancing medical research.

• Biomedical Databases and Platforms: Showcase the development and utilization of robust databases and platforms that facilitate efficient storage, organization, and retrieval of biomedical information, fostering collaboration and knowledge sharing.

• Integrative Biology: Delve into the synergistic integration of biological disciplines, such as genomics, proteomics, and metabolomics, with computational approaches, leading to comprehensive insights into biological systems.

• Pharmacogenomics: Explore the intersection of genomics and pharmacology, investigating how genetic factors influence drug response and developing personalized treatment strategies.

• Computational Biology: Uncover novel computational methods and algorithms used to model and analyze biological systems, furthering our understanding of complex biological phenomena.

• OMICS: Investigate various -omics disciplines (genomics, proteomics, metabolomics, transcriptomics, etc.) and their integration, enabling comprehensive analyses and revealing intricate molecular mechanisms.

• Personalized Medicine: Explore innovative approaches that aim to tailor medical treatments and interventions to individual patients, considering their unique genetic makeup, lifestyle, and environmental factors.

• Biomarkers, Drug Discovery, and Development: Present research on the identification and validation of biomarkers, as well as advancements in drug discovery and development processes, leading to improved diagnosis, treatment, and patient care.

• Explainable Artificial Intelligence: Shed light on the interpretability of artificial intelligence models, ensuring transparency and accountability in their decision-making processes within healthcare applications.

• Artificial Intelligence: Investigate the diverse applications of artificial intelligence in biomedicine, spanning from medical imaging analysis to clinical decision support systems, revolutionizing healthcare practices.