MATHEMATICAL MODELING IN BIOLOGY AND MEDICINE: CHALLENGES AND OPPORTUNITIES
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Abstract
Mathematical modeling has become indispensable in biology and medicine, offering insights into complex biological phenomena and informing medical decision-making. This paper explores the challenges and opportunities associated with mathematical modeling in these fields. We provide an overview of the importance of mathematical modeling, defining its role and purpose. Historical developments and key figures in the field are discussed, highlighting milestones and the evolution of mathematical techniques. Types of mathematical models, including deterministic, stochastic, and hybrid models, are examined, along with their applications in biology and medicine. We delve into population dynamics, epidemiology, evolutionary biology, neuroscience, and systems biology as areas where mathematical modeling has made significant contributions. Additionally, we explore its applications in medicine, including pharmacokinetics, disease modeling, cancer modeling, cardiovascular modeling, and personalized medicine. Challenges such as data availability, model complexity, validation, and interdisciplinary collaboration are identified, along with recommendations for addressing these challenges. Through interdisciplinary collaboration and innovative approaches, mathematical modeling continues to hold promise for transformative breakthroughs in biology and medicine.
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