Researchers have developed a system for extracting relevant information from optical character recognition (OCR) clinical reports. The system uses a technique called semi-structured extraction to identify key fields in the reports and improve performance. Experiments on real-world data from over 20 hospitals showed that covering 90 top keys led to significant improvements in accuracy, with F1 scores of 0.839 and 0.893 under exact match and boundary-tolerant matching, respectively. The method relies on a language-agnostic key-value organization and can be adapted to other settings. --- Why it matters: This research matters because it addresses the challenge of integrating clinical reports from different healthcare institutions, which is crucial for patient care and longitudinal review. By improving the extraction of relevant information from OCR reports, this system can help reduce data silos and enhance EHR integration. Source: https://arxiv.org/abs/2605.09440