Quantifying Uncertainty: Potential Medical Applications of the Heston Model of Financial Stochastic Volatility

Abstract

The Heston model, widely used in financial markets to characterize stochastic volatility, may have innovative applications to predict volatility in medicine and healthcare. This article hypothesizes potential uses of the Heston model to quantify volatility in epidemiology, pharmacology, healthcare operations, medical imaging, and biological systems. Conceptually, the ability of the model to quantify unpredictability could provide insight into complex medical processes with inherent variability. Specific ideas proposed include modeling disease spread dynamics, optimizing personalized drug dosing, forecasting healthcare service demand, analyzing signal fluctuations in medical images, and elucidating variability in biological systems such as heart rate and neural activity. However, significant research and rigorous testing would be required to determine the feasibility and validity of applying the Heston model in these contexts. Tailoring the model to capture many interacting variables in biological and medical systems poses challenges. Nonetheless, the hypothetical connections between the Heston model’s capabilities to predict volatility and potential medical applications merit further exploration.