ReviewCardiology journal2020
Artificial intelligence and automation in valvular heart diseases.
Review in Cardiology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses 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
13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 26 citations in OpenAlex.
- Artificial Intelligence in the Heart of Medicine: A Systematic Approach to Transforming Arrhythmia Care with Intelligent Systems.Current cardiology reviews · 2025Pooled it
- Current hotspot and study trend of transcatheter aortic valve replacement, a bibliometric analysis from 2009 to 2023.Frontiers in cardiovascular medicine · 2025Pooled it
- Proposing the ValvUS approach: integrating bedside tests and ultrasonography for severe valvular heart disease diagnosis.Einstein (Sao Paulo, Brazil) · 2026Review
- Review
- An efficient network with state space model under evidential training for fetal echocardiography standard view recognition.Medical & biological engineering & computing · 2025Article
- Artificial intelligence in cardiovascular procedures: a bibliometric and visual analysis study.Annals of medicine and surgery (2012) · 2025Review
- Artificial Intelligence in Cardiac Surgery: Transforming Outcomes and Shaping the Future.Clinics and practice · 2025Review
- Clinical applications of artificial intelligence and machine learning in neurocardiology: a comprehensive review.Frontiers in cardiovascular medicine · 2025Review
- The Role of Artificial Intelligence and Machine Learning in Cardiovascular Imaging and Diagnosis.Cureus · 2024Review
- Early Diagnosis of Cardiovascular Diseases in the Era of Artificial Intelligence: An In-Depth Review.Cureus · 2024Review
- Artificial Intelligence-Based Prediction of Cardiovascular Diseases from Chest Radiography.Journal of imaging · 2023Review
- Construction and validation of a method for automated time label segmentation of heart sounds.Frontiers in artificial intelligence · 2023Article
- Artificial intelligence for the echocardiographic assessment of valvular heart disease.Heart (British Cardiac Society) · 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
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is gradually changing every aspect of social life, and healthcare is no exception. The clinical procedures that were supposed to, and could previously only be handled by human experts can now be carried out by machines in a more accurate and efficient way. The coming era of big data and the advent of supercomputers provides great opportunities to the development of AI technology for the enhancement of diagnosis and clinical decision-making. This review provides an introduction to AI and highlights its applications in the clinical flow of diagnosing and treating valvular heart diseases (VHDs). More specifically, this review first introduces some key concepts and subareas in AI. Secondly, it discusses the application of AI in heart sound auscultation and medical image analysis for assistance in diagnosing VHDs. Thirdly, it introduces using AI algorithms to identify risk factors and predict mortality of cardiac surgery. This review also describes the state-of-the-art autonomous surgical robots and their roles in cardiac surgery and intervention.
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.