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Published on: September 20, 2018
Applications of Natural Language Processing for Automated Clinical Data Analysis in Orthopaedics
Yasir AlShehri1, Arashdeep Sidhu, Laks V S Lakshmanan
1From the Department of Orthopedics, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia (AlShehri), the Department of Orthopaedics, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada (Sidhu and Lefaivre), and the Department of Computer Science, The University of British Columbia, Vancouver, BC, Canada (Lakshmanan).
Abstract:
Natural language processing is an exciting and emerging field in health care that can transform the field of orthopaedics. It can aid in the process of automated clinical data analysis, changing the way we extract data for various purposes including research and registry formation, diagnosis, and medical billing. This scoping review will look at the various applications of NLP in orthopaedics. Specific examples of NLP applications include identification of essential data elements from surgical and imaging reports, patient feedback analysis, and use of AI conversational agents for patient engagement. We will demonstrate how NLP has proven itself to be a powerful and valuable tool. Despite these potential advantages, there are drawbacks we must consider. Concerns with data quality, bias, privacy, and accessibility may stand as barriers in the way of widespread implementation of NLP technology. As natural language processing technology continues to develop, it has the potential to revolutionize orthopaedic research and clinical practices and enhance patient outcomes.

