AI in Clinical Data Management: Transforming the Future of Healthcare

Clinical Data Management (CDM) is a pivotal component of modern healthcare and clinical research, ensuring the accurate collection, integration, and validation of patient data. With the increasing volume and complexity of clinical data, Artificial Intelligence (AI) has emerged as a transformative force, automating data capture, ensuring data quality, and enabling predictive analytics. This paper explores the application of AI in CDM, providing a comprehensive review of current methodologies, tools, and their implications on clinical trials and patient care. It highlights AI's role in enhancing data accuracy, reducing trial timelines, and improving decision-making, while addressing ethical and regulatory challenges. Through a systematic literature review and analysis of case studies, the study concludes that integrating AI into CDM systems offers substantial benefits, although it requires careful implementation and oversight.

Authors

Publication Details

Journal
International Journal on Science and Technology
Published
2025-06-12
DOI
https://doi.org/10.71097/ijsat.v16.i2.6191
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

AI in Clinical Data Management: Transforming the Future of Healthcare

Andreas Baur, Tapas Kumar Maji, Smita Halder, R Yasmin
International Journal on Science and Technology
Artificial Intelligence in Healthcare and Education
article

AI in Clinical Data Management: Transforming the Future of Healthcare

Andreas Baur, Tapas Kumar Maji, Smita Halder, R Yasmin
article en

Abstract

Clinical Data Management (CDM) is a pivotal component of modern healthcare and clinical research, ensuring the accurate collection, integration, and validation of patient data. With the increasing volume and complexity of clinical data, Artificial Intelligence (AI) has emerged as a transformative force, automating data capture, ensuring data quality, and enabling predictive analytics. This paper explores the application of AI in CDM, providing a comprehensive review of current methodologies, tools, and their implications on clinical trials and patient care. It highlights AI's role in enhancing data accuracy, reducing trial timelines, and improving decision-making, while addressing ethical and regulatory challenges. Through a systematic literature review and analysis of case studies, the study concludes that integrating AI into CDM systems offers substantial benefits, although it requires careful implementation and oversight.

International Journal on Science and TechnologyVol. 16(2)
Peace, Justice and strong institutions
Openalex Percentile: Top 91%
Artificial Intelligence in Healthcare and Education
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