ArticleStudies in health technology and informatics2023
How Good Is ChatGPT for Medication Evidence Synthesis?
Article in Studies in health technology and informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The emergence of large language models as tools in literature reviews: a large language model-assisted systematic review.Journal of the American Medical Informatics Association : JAMIA · 2025Pooled it
- Enhanced pre-recruitment framework for clinical trial questionnaires through the integration of large language models and knowledge graphs.Scientific reports · 2025Article
- ChatGPT-4 for addressing patient-centred frequently asked questions in age-related macular degeneration clinical practice.Eye (London, England) · 2025Article
- The ethics of ChatGPT in medicine and healthcare: a systematic review on Large Language Models (LLMs).NPJ digital medicine · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
With its seeming competence to mimic human responses, ChatGPT, an emerging AI-powered chatbot, has spurred great interest. This study aims to explore the role of ChatGPT in synthesizing medication literature and compare it with a hybrid summarization system. We tested ten medications' effectiveness with reference to their definitions and descriptions extracted from DrugBank. ChatGPT could generate coherent summaries that are not backed by evidence. In contrast, our approach can provide a highly structured and concise synthesis of related evidence, but the resulting summary is not as fluent and convincing as ChatGPT. Therefore, we recommend integrating both techniques to achieve the best performance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.