Computational Modelling and Analytical Framework for Medical Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E3: Mathematical Biology".
Deadline for manuscript submissions: closed (30 September 2024) | Viewed by 3792
Special Issue Editors
Interests: mathematical modelling; numerical analysis for PDEs; computational modelling and analytical framework for cancer cell invasion
Special Issue Information
Dear Colleagues,
The Special Issue "Computational Modelling and Analytical Framework for Medical Applications" aims to summarize recent developments and trends in computational modeling and analytical frameworks for medical applications. The scope of this Special Issue covers the application of mathematical, computational, and statistical methods in order to understand and predict medical processes, develop new medical technologies, diagnose and treat diseases, and analyze medical data. It will provide a platform for interdisciplinary exchange between mathematicians, computer scientists, medical researchers, and engineers working in this field.
The Special Issue will cover a wide range of topics including, but not limited to, the following:
- Medical image analysis and processing;
- Computational modeling of physiological systems;
- Single-scale and multi-scale mathematical models (describing single-scale and multi-scale physiological systems);
- Statistical learning for medical data analysis;
- Parameter identification for deterministic and stochastic systems;
- Medical device design and optimization;
- Predictive and personalized medicine;
- Medical decision-making and diagnosis;
- Simulation of medical procedures and treatments;
- Applications of machine learning and artificial intelligence in medicine;
- Big data analysis in medical research.
Dr. Dumitru Trucu
Prof. Dr. Raluca Eftimie
Guest Editors
Manuscript Submission Information
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Keywords
- medical applications
- computational modeling
- analytical framework
- mathematical methods
- medical data analysis
- medical image analysis
- medical device design
- machine learning
- artificial intelligence
- big data analysis
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