UC Santa Cruz

The primary objective of this thesis is to expedite the intricate process of wound healing through a multifaceted computational approach. Our journey commences by delving into the relationship between neurites and wound recovery, a relatively unexplored yet pivotal facet of this biological phenomenon.

In the initial phase of our research, we introduce an innovative computational methodology designed to establish correlations between neuronal activity and the progression of wound healing. Employing advanced data analytic techniques, we unravel the pivotal role neurites play in the overall healing process. This newfound understanding significantly enriches our comprehension of wound healing mechanisms.

The second phase of our study harnesses a state-of-the-art deep learning algorithm. This algorithm is engineered to identify and quantify neurites within microscopic images autonomously. This high-throughput approach equips us with the ability to investigate how various pharmaceutical interventions impact neurite growth meticulously. This foundational research lays the cornerstone for the development of optimized strategies aimed at expediting wound healing.

As we progress to the final phase of our investigation, we take a more comprehensive approach. Here, we introduce a Deep Reinforcement Learning (DRL) model, which is tailored to optimize wound healing based on the analysis of wound images. While the DRL model does not directly incorporate neurite data, the insights gleaned from our earlier studies significantly enhance the model's effectiveness. Trained to recognize various stages of wound development through image analysis, the DRL model adapts in real time, offering a flexible framework for making critical medical decisions.

This thesis, commencing with a focused exploration of neurites and culminating in applying DRL to wound images, signifies a substantial breakthrough in computational medicine. The fusion of deep learning and reinforcement learning techniques presents a potent arsenal for comprehending and enhancing the intricate biological processes underlying wound healing. Ultimately, this research lays the groundwork for more efficient and personalized therapeutic approaches in wound care, promising significant advancements in patient outcomes and healthcare practices.