ArticleFrontiers in cardiovascular medicine2023
Artificial intelligence guidance of advanced heart failure therapies: A systematic scoping review.
Article in Frontiers in cardiovascular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Can algorithms come to the rescue of a failing heart? Machine learning, artificial intelligence, and decision-making in cardiogenic shock.Journal of anesthesia, analgesia and critical care · 2026Article
- Predicting Simultaneous Heart Kidney Allocation and Posttransplant Adverse Kidney Outcomes.Kidney international reports · 2026Article
- Key Concepts in Machine Learning and Clinical Applications in the Cardiac Intensive Care Unit.Current cardiology reports · 2025Review
- Interoception, cardiac health, and heart failure: The potential for artificial intelligence (AI)-driven diagnosis and treatment.Physiological reports · 2025Review
- From patterns to prognosis: machine learning-derived clusters in advanced heart failure.Frontiers in cardiovascular medicine · 2025Article
- The intelligent Impella: Future perspectives of artificial intelligence in the setting of Impella support.ESC heart failure · 2024Review
- 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
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Artificial intelligence can recognize complex patterns in large datasets. It is a promising technology to advance heart failure practice, as many decisions rely on expert opinions in the absence of high-quality data-driven evidence. Methods: We searched Embase, Web of Science, and PubMed databases for articles containing "artificial intelligence," "machine learning," or "deep learning" and any of the phrases "heart transplantation," "ventricular assist device," or "cardiogenic shock" from inception until August 2022. We only included original research addressing post heart transplantation (HTx) or mechanical circulatory support (MCS) clinical care. Review and data extraction were performed in accordance with PRISMA-Scr guidelines. Results: Of 584 unique publications detected, 31 met the inclusion criteria. The majority focused on outcome prediction post HTx ( Conclusion: Our review showed mounting innovation in AI application in management of MCS and HTx, with the largest evidence showing improved mortality outcome prediction.
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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.