Combining Physics-Based Modeling and Data Analytics Methods To Develop a Digital Twin for Ocular Applications
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Understanding the behavior of the human eye is challenging due to the complex interactions between various physical phenomena, such as heat transfer, fluid dynamics, and tissue deformation. While medical data offer valuable insights into ocular physiopathology, they can be scarce and noisy, and the multitude of influencing factors makes it difficult to isolate the contributions of individual mechanisms. Developing a robust and accurate digital twin for ocular applications can enhance our understanding of the physiological system by integrating the governing mechanisms and data variability. This talk presents our ongoing efforts to develop a digital twin, focusing on the thermo-fluid dynamics governing aqueous humor flow in the anterior and posterior chambers and its coupling with heat transfer throughout the eyeball. We will illustrate these developments, discuss their applications in ocular physiology and treatment, and address remaining challenges, including inverse problems and parameter identification.
