ArticleFrontiers in public health2022
Scoping review of the current landscape of AI-based applications in clinical trials.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed, 41 citations in OpenAlex.
- AI-based augmentation of oncology clinical trials.Nature reviews. Clinical oncology · 2026Review
- Applications of artificial intelligence for real-world evidence generation: a protocol for a living scoping review.BMJ open · 2026Article
- Medical clinical minds meet artificial intelligence: Italian physicians' knowledge, attitudes, and concordance between Italian physicians and AI-generated diagnoses. A national cross-sectional study.Frontiers in digital health · 2026Article
- [Clinical research and medical ethics in the era of artificial intelligence].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2025Article
- Artificial intelligence for optimizing recruitment and retention in clinical trials: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Machine Learning Approaches for the Prediction of Postoperative Major Complications in Patients Undergoing Surgery for Bowel Obstruction.Journal of personalized medicine · 2024Article
- A Method to Redesign and Simplify Schedules of Assessment and Quantify the Impacts. Applications to Merck Protocols.Therapeutic innovation & regulatory science · 2024Article
- AI-Assisted Detection of Biomarkers by Sensors and Biosensors for Early Diagnosis and Monitoring.Biosensors · 2024Review
- Artificial Intelligence in Pediatric Emergency Medicine: Applications, Challenges, and Future Perspectives.Biomedicines · 2024Review
- Digital Technology Applications in the Management of Adverse Drug Reactions: Bibliometric Analysis.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Artificial Intelligence in Pediatrics: Learning to Walk Together.Turkish archives of pediatrics · 2024Article
- Methodological review to develop a list of bias items for adaptive clinical trials: Protocol and rationale.PloS one · 2024Article
- Computational methods in glaucoma research: Current status and future outlook.Molecular aspects of medicine · 2023Review
- Must-have Qualities of Clinical Research on Artificial Intelligence and Machine LearningBalkan medical journal · 2023Review
- The role of artificial intelligence in hastening time to recruitment in clinical trials.BJR open · 2023Review
- Natural Language Processing in Clinical Research Recruitment: A Scoping Review Enriched with Stakeholder Insights.Ethics & human researchArticle
- Digital health technologies and artificial intelligence in cardiovascular clinical trials: A landscape of the European space.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
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Clinical trials are essential for bringing new drugs, technologies and procedures to the market and clinical practice. Considering the design and the four-phase development, only 10% of them complete the entire process, partly due to the increasing costs and complexity of clinical trials. This low completion rate has a huge negative impact in terms of population health, quality of care and health economics and sustainability. Automating some of the process' tasks with artificial intelligence (AI) tools could optimize some of the most burdensome ones, like patient selection, matching and enrollment; better patient selection could also reduce harmful treatment side effects. Although the pharmaceutical industry is embracing artificial AI tools, there is little evidence in the literature of their application in clinical trials. Methods: To address this issue, we performed a scoping review. Following the PRISMA-ScR guidelines, we performed a search on PubMed for articles on the implementation of AI in the development of clinical trials. Results: The search yielded 772 articles, of which 15 were included. The articles were published between 2019 and 2022 and the results were presented descriptively. About half of the studies addressed the topic of patient recruitment; 12 articles reported specific examples of AI applications; five studies presented a quantitative estimate of the effectiveness of these tools. Conclusion: All studies present encouraging results on the implementation of AI-based applications to the development of clinical trials. AI-based applications have a lot of potential, but more studies are needed to validate these tools and facilitate their adoption.
Indexed as
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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.