<ul data-eligibleForWebStory="false"><li>The paper introduces the Medical Data Pecking approach for evaluating the quality of structured medical data used in Electronic Health Records (EHRs) for research and AI training.</li><li>The approach utilizes unit testing and coverage concepts from software engineering to identify data quality concerns and includes the Medical Data Pecking Tool (MDPT).</li><li>MDPT was tested on three datasets and successfully identified non-aligned or non-conforming data issues, demonstrating its effectiveness in improving data quality for research purposes.</li><li>The approach incorporates external medical knowledge to enhance context-sensitive data quality testing and aims to address challenges in data quality assessment for research purposes.</li></ul>

Medical Data Pecking: A Context-Aware Approach for Automated Quality Evaluation of Structured Medical Data

Discover more