ReviewCardiovascular and interventional radiology2022
Prime Time for Artificial Intelligence in Interventional Radiology.
Review in Cardiovascular and interventional radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The use of machine learning in transarterial chemoembolisation/transarterial embolisation for patients with intermediate-stage hepatocellular carcinoma: a systematic review.La Radiologia medica · 2025Pooled it
- Imaging-Based Artificial Intelligence in Vascular and Interventional Radiology: A Narrative Review.Journal of imaging informatics in medicine · 2026Review
- A Review on Artificial Intelligence as a Solution to Burnout in Interventional Radiology.Cardiovascular and interventional radiology · 2026Review
- A Promptable 3D-CT Foundation Model-Based Approach for Pulmonary Embolism.Cardiovascular and interventional radiology · 2026Article
- Human-AI Interaction in Interventional Radiology: A Narrative Review of Current Applications, Challenges, and Future Directions.Journal of imaging · 2026Review
- Machine Learning and MRI-Based Whole-Organ Magnetic Resonance Imaging Score (WORMS): A Novel Approach to Enhancing Genicular Artery Embolization Outcomes in Knee Osteoarthritis.Cardiovascular and interventional radiology · 2025Article
- Artificial Intelligence Applications in Interventional Radiology.Journal of personalized medicine · 2025Review
- Interventional Radiology: Towards Personalized Medicine.Journal of personalized medicine · 2025Article
- AI and Interventional Radiology: A Narrative Review of Reviews on Opportunities, Challenges, and Future Directions.Diagnostics (Basel, Switzerland) · 2025Review
- Applications of artificial intelligence in interventional oncology: An up-to-date review of the literature.Japanese journal of radiology · 2025Review
- Artificial Intelligence in Neuroendovascular Procedures.Journal of neuroendovascular therapy · 2025Review
- Review
- Machine Learning Predicts Unplanned Care Escalations for Post-Anesthesia Care Unit Patients during the Perioperative Period: A Single-Center Retrospective Study.Journal of medical systems · 2024Article
- Article
- Artificial intelligence in interventional radiology: state of the art.European radiology experimental · 2024Review
- Enhancing patient outcomes: the role of clinical utility in guiding healthcare providers in curating radiology AI applications.Frontiers in digital health · 2024Article
- The Utility of Multimodal Imaging and Artificial Intelligence Algorithms for Overlying Two Volumes in the Decision Chain for the Treatment of Complex Pathologies in Interventional Neuroradiology-A Case Series Study.Life (Basel, Switzerland) · 2023Article
- Artificial Intelligence, Augmented Reality, and Virtual Reality Advances and Applications in Interventional Radiology.Diagnostics (Basel, Switzerland) · 2023Review
- Generating synthetic multidimensional molecular time series data for machine learning: considerations.Frontiers in systems biology · 2023Article
- Precision Imaging Guidance in the Era of Precision Oncology: An Update of Imaging Tools for Interventional Procedures.Journal of clinical medicine · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Machine learning techniques, also known as artificial intelligence (AI), is about to dramatically change workflow and diagnostic capabilities in diagnostic radiology. The interest in AI in Interventional Radiology is rapidly gathering pace. With this early interest in AI in procedural medicine, IR could lead the way to AI research and clinical applications for all interventional medical fields. This review will address an overview of machine learning, radiomics and AI in the field of interventional radiology, enumerating the possible applications of such techniques, while also describing techniques to overcome the challenge of limited data when applying these techniques in interventional radiology. Lastly, this review will address common errors in research in this field and suggest pathways for those interested in learning and becoming involved about AI.
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.