Dr. Hilal Maradit Kremers will give the fourth talk in The USM Data Science Ensemble, a seminar series focused on the intersection of data science and real-world applications. We invite you to join us for this in-depth look at a practical application of data science in the real world, by joining this moderated Zoom link.
In Dr. Kremers' talk, "Our adventure with AI methods in orthopedics: lessons learned," she will explore orthopedic surgical procedures, and in particular, total joint arthroplasty (TJA) of the hip and knee joints. They are the most common and the fastest-growing surgeries in the US, however, the evidence for TJA practice and technologies is based on imperfect and incomplete data. The lack of high-quality phenotypic data is a critical barrier to progress in improving TJA outcomes. TJA-specific phenotypic data remain embedded in the unstructured text of the EHR and/or serial TJA radiographs. Over the past few years, we’ve established an interdisciplinary team, and have been developing several natural language processing (NLP) and deep learning computer vision algorithms to better phenotype TJA patients. Dr. Kremers will give examples from these projects and outline how the team learned to work together and be productive in developing clinically applicable AI tools in orthopedics.
Dr. Hilal Maradit Kremers is an established musculoskeletal epidemiologist focused primarily on orthopedics research. She is the methodology core director for the NIH- funded core center for clinical research in total joint arthroplasty (American Joint Replacement Research Collaborative - AJRR-C), and her team provides methodological expertise and access to large data resources and expertise to facilitate innovative, methodologically rigorous, and interdisciplinary clinical research in orthopedics. Her ongoing NIH-funded research program examines the risk and predictors of neurotoxicity and cardiotoxicity in arthroplasty patients. She collaborates with an interdisciplinary team of investigators for the development of artificial intelligence (AI) applications in orthopedics research and practice. In her talk, she will present some of the projects performed at Mayo Clinic and her experiences while working with a large team of surgeons, data scientists, informaticians, and statisticians.