Articles
AI-driven Electronic Health Record Curation for Clinical Research: Developing AI algorithms to curate electronic health records for use in clinical research studies
Published 28-09-2024
Keywords
- Electronic Health Records,
- Healthcare Technology
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
How to Cite
[1]
Dr. Hassan Mahmoud, “AI-driven Electronic Health Record Curation for Clinical Research: Developing AI algorithms to curate electronic health records for use in clinical research studies”, Hong Kong J. of AI and Med., vol. 4, no. 2, pp. 9–15, Sep. 2024, Accessed: Sep. 18, 2024. [Online]. Available: https://hongkongscipub.com/index.php/hkjaim/article/view/34
Abstract
In the realm of clinical research, the extraction and curation of relevant information from electronic health records (EHRs) pose significant challenges. Manual curation is labor-intensive, time-consuming, and prone to errors. This paper proposes an AI-driven approach to streamline the curation process, leveraging machine learning algorithms to extract key data points from EHRs efficiently. By automating this process, researchers can expedite data collection, enhance data quality, and ultimately improve the efficiency of clinical research studies.
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