ReviewThrombosis journal2025
Artificial intelligence in thrombosis: transformative potential and emerging challenges.
Review in Thrombosis journal, 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.
- Contemporary Challenges in Venous Thromboembolism: Evolving Populations and Implications for Management and Risk Stratification.Journal of clinical medicine · 2026Review
- Exploring the association between gut microbiota and venous thromboembolism using a Mendelian randomization analysis.Archives of medical science : AMS · 2026Article
- Article
- Construction and verification of a nomogram to predict the probability of venous thromboembolism in lung cancer patients.Frontiers in molecular biosciences · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE), continues to pose significant clinical challenges despite advancements in medical care. Artificial intelligence (AI) presents promising opportunities to enhance the diagnosis, prediction, and management of VTE. This review examines the transformative potential of AI in thrombosis care, highlighting both the potential benefits and the challenges that need to be addressed. Through an analysis of current applications and future directions, the review underscores AI's role in advancing VTE management and improving clinical outcomes.
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.