Proposal for Using AI to Assess Clinical Data Integrity and Generate Metadata: Algorithm Development and Validation.
Journal:
JMIR medical informatics
Published Date:
Jun 30, 2025
Abstract
BACKGROUND: Evidence-based medicine combines scientific research, clinical expertise, and patient preferences to enhance the patient outcomes and improve health care quality. Clinical data are crucial in aligning medical decisions with evidence-based practices, whether derived from systematic research or real-world data sources. Quality assurance of clinical data, mainly through predictive quality algorithms and machine learning, is essential to mitigate risks such as misdiagnosis, inappropriate treatment, bias, and compromised patient safety. Furthermore, excellent quality of clinical data is a prerequisite for the replication of research results in order to gain insights from practice and real-world evidence.
