ArticleBritish journal of biomedical science2025
Artificial Intelligence in Biomedical Sciences: A Scoping Review.
Article in British journal of biomedical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
- Can artificial intelligence in orthopantomography advance dental diagnostics through automated image analysis?Frontiers in radiology · 2026Review
- An Analysis of the Career Pathway of Clinical Laboratory Scientists: Identifying Access Barriers and Best Practice to Increase Diversity in the Workforce.British journal of biomedical science · 2026Review
- Review
- Role of artificial intelligence in bacterial diagnostics and surveillance of anti-microbial resistance.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) is increasingly playing important roles in healthcare diagnosis, treatment, monitoring, and prevention of diseases. Despite this widespread implementation of AI in biomedical sciences, it has yet to be characterized. Aim: The aim of this scoping review is to explore AI in biomedical sciences. Specific objectives are to synthesize six scopes addressing the characteristics of AI in biomedical sciences and to provide in-depth understanding of its relevance to education. Methods: This scoping review has been developed according to Arksey and O'Malley frameworks. PubMed, Embase, and Web of Science databases were searched using broad search terms without restrictions. Citations were imported into EndNote for screening and extraction. Data were categorized and synthesized to define six scopes discussing AI in biomedical sciences. Results: A total of 2,249 articles were retrieved for screening and extraction, and 192 articles were included in this review. Six scopes were synthesized from the extracted data: Scope (1): AI in biomedical sciences by decade, highlighting the increasing number of publications on AI in biomedical sciences. Scope (2): AI in biomedical sciences by region, showing that publications on AI in biomedical sciences mainly originate from high-income countries, particularly the USA. Scope (3): AI in biomedical sciences by model, identifying machine learning as the most frequently reported model. Scope (4): AI in biomedical sciences by discipline, with microbiology the discipline most commonly associated with AI in biomedical sciences. Scope (5): AI in biomedical sciences education, which was limited to only six studies, indicating a gap in research on the educational application of AI in biomedical sciences. Scope (6): Opportunities and limitations of AI in biomedical sciences, where major reported opportunities include efficiency, accuracy, universal applicability, and real-world application. Limitations include; model complexity, limited applicability, and algorithm robustness. Conclusion: AI has generally been under characterized in the biomedical sciences due to variability in AI models, disciplines, and perspectives of applicability.
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.