Leveraging artificial intelligence to enhance systematic reviews in health research: advanced tools and challenges
Artificial Intelligence (AI) is transforming systematic reviews (SRs) in health research by automating processes such as study screening, data extraction, and quality assessment. This perspective highlights recent advancements in AI tools that enhance efficiency and accuracy in SRs. It discusses the benefits, challenges, and future directions of AI integration, emphasising the need for human oversight to ensure the reliability of AI outputs in evidence synthesis and decision-making in healthcare.
Authors
- Kiok Liang Teow
- Rupesh Agrawal (ORCID: https://orcid.org/0000-0002-6662-5850)
- Chun Wei Yap (ORCID: https://orcid.org/0000-0002-2004-3492)
- M. Singer (ORCID: https://orcid.org/0000-0002-5889-9704)
- Lixia Ge (ORCID: https://orcid.org/0000-0001-8080-7020)
- John Abisheganaden (ORCID: https://orcid.org/0000-0002-3192-317X)
- Joseph Antonio De Castro Molina (ORCID: https://orcid.org/0000-0003-2960-7861)
- Palvannan Kannapiran
Institutions
- SingHealth (SG)
- Nanyang Technological University (SG)
- Tan Tock Seng Hospital (SG)
- Yale University (US)
Publication Details
- Journal
- Systematic Reviews
- Published
- 2024-10-25
- DOI
- https://doi.org/10.1186/s13643-024-02682-2
- Citations
- 49
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 5.89