A new study published in the journal Frontiers in Neurology demonstrates how artificial intelligence can be used to identify potential rare disease patients using retrospective electronic medical records (EHRs).
A new study published in the journal Frontiers in Neurology demonstrates how artificial intelligence can be used to identify potential rare disease patients using retrospective electronic medical records (EHRs). The study focuses on Pompe disease, but the findings are applicable to other pathologies.
To demonstrate its feasibility, the researchers applied an AI-based approach to examine 15-year-old EHRs, achieving a specificity of 18.27% and greatly reducing the need for manual review by the physician. This represents a significant improvement in diagnostic efficiency, which is crucial in Pompe disease and many other rare diseases, where early diagnosis is key to optimizing prognosis and treatment outcomes.
Although this study was performed only on Pompe disease, the AI tool used can be applied to several rare diseases. As such, the approach suggested by the authors would help improve diagnosis and care for all rare disease patients. The authors propose an automated process that can run in the background, screening all patients visiting a given healthcare facility and complementing existing approaches, such as newborn screening. Such a strategy provides a scalable and resource-efficient solution to improve diagnostic access and overall patient outcomes.
Benefits of using AI with electronic medical records
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