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Updated: Jul 13, 2025
05:47
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
255
Artificial Intelligence-Generated Scientific Literature: A Critical Appraisal
Justyna Zybaczynska1, Matthew Norris1, Sunjay Modi1
1Section of Allergy, Asthma & Immunology, Department of Medicine, Pennsylvania State University College of Medicine, Hershey, Pa.
The Journal of Allergy and Clinical Immunology. in Practice
|October 13, 2023
Summary
Artificial intelligence (AI) tools like GPT-4 can generate medical literature quickly, but reviews show the content may lack depth and contain inaccuracies. Rigorous validation is essential before using AI-generated medical content.
Area of Science:
- Medical Informatics
- Artificial Intelligence in Medicine
- Scientific Literature Synthesis
Background:
- Review articles are crucial for medical decision-making and research.
- Artificial intelligence (AI) offers potential for transforming medical literature synthesis.
- Open AI's GPT-4 is an advanced AI tool capable of generating medical literature rapidly.
Purpose of the Study:
- To critically appraise AI-synthesized allergy-focused minireviews.
- Evaluate the accuracy and quality of AI-generated medical content in Allergy/Immunology.
Main Methods:
- GPT-4 Chatbot generated two 1,000-word reviews on hereditary angioedema and eosinophilic esophagitis.
- Authors used the Joanna Briggs Institute (JBI) tool for appraisal.
- Evaluated language, reference quality, and content accuracy.
Main Results:
- AI-generated content was articulate but lacked depth and analytical rigor.
- Inaccurate information and fabricated references were identified.
- AI primarily used freely available resources, missing critical details.
Conclusions:
- AI has the potential to revolutionize medical literature synthesis.
- Inaccurate and fabricated information necessitate rigorous AI tool evaluation.
- Validation is critical, especially for AI-generated content in specialized fields with limited resources.
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