AI Prediction Models for ACL Injury Risk and Recovery Time

Harnessing AI to predict ACL injuries and recovery time: turning athlete data into tools for prevention, performance, and faster comeback.

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Ever since I was a child, table tennis was more than a sport. It was my passion, my identity, and the lens through which I understood discipline, perseverance, and hard work. I became the regional champion for U15 boys and at one point was ranked number five in the nation. Every victory, every late-night practice, and every tournament shaped who I was and who I wanted to become. Then everything came crashing down. During a soccer class in PE, I tore my ACL right before a national table tennis tournament. In that instant, the sport that had defined my life was taken away. The pain was overwhelming, both physically and emotionally. I had trained my entire life for moments like that tournament, and suddenly, all of it felt lost. The injury forced me to confront not only my limitations but also the fragility of the dreams I had built with my own hands. In the midst of that despair, I realized that my experience was not just personal. Thousands of athletes face ACL injuries every year, and recovery is often uncertain, long, and poorly predicted. I decided to turn my pain into purpose. I vowed to transform my own suffering into something that could help others prevent injuries, recover more effectively, and pursue their passions without fear.

This mission became the heart of Paddle Forward Foundation, a nonprofit I founded to promote health, community engagement, and resilience through table tennis. At the Barbara Lee Senior Center, we have over forty-five active members. I have organized table tennis programs, fundraiser tournaments, and health education campaigns, all designed to bring the community together and encourage lifelong wellness. We have partnered with organizations such as HotSpotStudios and Caring Hands Caregivers to create meaningful experiences, and a core part of our work is giving back to research that can make a real difference. Paddle Forward Foundation has raised thousands of dollars and donates a significant portion of its proceeds to ACL research, supporting studies that aim to prevent injuries and improve recovery outcomes for athletes. Beyond sport, the foundation serves as a vehicle for mentorship, fostering connection between generations, and teaching life skills like focus, perseverance, and resilience. It embodies the principle that personal passion can be transformed into communal impact and that the lessons learned from overcoming adversity can be shared to help others.

My injury also inspired me to pursue research to better understand ACL injuries and recovery. I worked with PhDs and professional researchers across multiple programs, including the Lumiere Education Research Scholar Program, the Young Researchers Institute, and as a Co-Associate at ThinkNeuro Research Internship where I led a team of interns. I completed a research batch at NeuraVia Research Inc. and received a Certification of Distinction. I achieved Mentor Excellence by guiding a group of mentees through research projects and gained hands-on lab experience such as Gel Electrophoresis at BioCurious. These experiences taught me to collect and analyze data, design experiments, lead teams, and bridge research with real-world applications. This combination of mentorship, in-person lab work, and applied research gave me the technical skills and confidence to take on my ACL project for the Eurkathon.

During the five-week Eurkathon, I built the entire AI-assisted prediction model myself. I collected and cleaned basketball athlete performance and injury datasets, carefully handling missing values and normalizing metrics. I used Google Sheets and pivot tables to organize the data, summarize trends, and identify key patterns. I then leveraged Python to perform advanced data analysis, generate plots and graphs, and visualize correlations between player performance and injury risk. Using the insights from this analysis, I implemented machine learning algorithms to predict both ACL injury risk and estimated recovery duration. I iteratively tested the models using metrics like accuracy, precision, and recall, refining them to ensure the results were interpretable and clinically meaningful. My goal was not just a high-performing model but a tool that could actually help athletes and clinicians make informed decisions.

The journey was extremely challenging. Recovering from my own ACL injury while managing schoolwork, and building a technical AI project tested my resilience and discipline. The datasets were limited and required careful integration, normalization, and handling missing or inconsistent information. Learning and implementing AI models in a compressed five-week timeline was intense, requiring rapid problem-solving, debugging, and iteration. Balancing the technical, practical, and community aspects of the project demanded unwavering focus and time management. Despite these obstacles, the project became a testament to turning personal adversity into opportunity, showing that pain can fuel meaningful action, innovation, and community impact.

This project is more than research. It represents the intersection of personal experience, athletic achievement, nonprofit leadership, and scientific exploration. For athletes, the AI models provide tools to prevent injuries and optimize recovery planning. For the community, Paddle Forward Foundation uses sports to teach resilience, health, and engagement. For me, this project transformed heartbreak into a lifelong mission: to use science, data, and community service to help others avoid the struggles I endured. It reflects the lessons, perseverance, and purpose I have built through years of sport, research, and service.

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