ReviewFrontiers in pharmacology2025
An artificial intelligence-aided scoping review of medicinal plant research in the Fertile Crescent.
Review in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Effectiveness of ChatGPT and DeepSeek in Urology Medical Education: Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Traditional Arabic and Islamic Medicine (TAIM) originated in the seventh century, but unlike Chinese and Ayurvedic knowledge, TAIM has not evolved through evidence-based research and commercialization. Today, while global interest in traditional medicine is growing, TAIM ancestral knowledge remains unknown and unexplored. The purpose of this study is to provide baseline information on the status of TAIM research to guide future research and contribute to the growth of the sector. The focus of the study is the Fertile Crescent, a region of the Arab World endowed with a rich and diverse eco-geography. The method adopted was a scoping review following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. The databases used included the Arab World Research Source: Al Masdar, CAB Direct, Iraqi Academic Scientific Journals, MEDLINE, Scopus, Web of Science and Google Scholar. The timeline of the search spanned from the database inception date to June 2024. The search led to 10,171 records which were subsequently reduced to 1,990 publications after deleting duplicates and performing a two-stage screening. Artificial intelligence (AI) technology was used to analyze the data focusing on reported plant species, treatment applications, study types and countries. The Generative Pretrained Transformer 4 (GPT-4) Turbo, a large language model, was used to extract the key features and the results were validated by the researchers. The findings revealed that the types of studies were mostly laboratory-based (86%), while few studies (14%) were field based. The top five treatment applications include cancer (29%), bacterial infections (22%), inflammation (12%), fungal infections (9%), and diabetes (8%). The most notable plant species that were under investigation in the various studies were
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.