Researchers Dr. Yuxiao Zhou, an assistant professor in the J. Mike Walker ’66 Department of Mechanical Engineering, along with Dr. Jaesung Lee, an assistant professor in the Wm Michael Barnes ’64 Department of Industrial and Systems Engineering at Texas A&M University, have received the 2024 Seed Program for AI, Computing, and Data Science award from the Texas A&M Institute of Data Science.

Their initiative, titled “Toward Smart Orthopedic Surgery Planning by using Physics-Informed Machine Learning,” was recognized as one of the top 10 proposals during a competitive process that included 39 submissions from various researchers across three institutions.

Dental implant procedures are vital for improving life quality, especially among the elderly. Nonetheless, their effectiveness hinges on achieving ideal mechanical stress levels in the adjacent bone during mastication to avert bone deterioration from inadequate loading and to prevent bone fractures from excessive stress.

The success of implants faces difficulties such as slow bone recovery and age-associated bone loss in older adults, along with variations in bone rigidity. Existing techniques for gauging bone stiffness tend to be invasive, computationally expensive, or lack precision, necessitating the development of creative and effective patient-centered solutions.

In response to these challenges, Zhou and Lee are creating a hybrid biomechanical physics-informed machine learning model. This innovative approach merges experimentally acquired bone deformation information with foundational physics and a strong machine learning architecture, allowing for accurate, customized forecasts of mechanical stress in the bone. This advancement serves as an effective instrument for tailoring dental surgical plans to individual patients, enhancing bone recovery and promoting lasting success of implants.

“Our model is set to transform surgical planning by providing tailored, computationally efficient treatment strategies with reliable results,” Zhou stated.

The project exemplifies interdisciplinary cooperation, utilizing Lee’s knowledge in machine learning for healthcare systems to tackle a persistent clinical issue. The achievements of this research may extend beyond dental implants, paving the way for improvements in other surgical fields within the healthcare sector.

This accolade underscores Texas A&M’s dedication to research in AI, computing, and data science that generate solutions with tangible effects.