ReviewFrontiers in cardiovascular medicine2022
Big Data in Cardiology: State-of-Art and Future Prospects.
Review in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Integrating Large-Scale Data Analytics for Cardiovascular Disease Prediction: A Scoping Review.Healthcare informatics research · 2025Article
- Digital health: current applications, challenges, and future directions for enhancing healthcare quality and safety.Frontiers in public health · 2025Review
- Trustworthy and ethical AI-enabled cardiovascular care: a rapid review.BMC medical informatics and decision making · 2024Review
- Artificial Intelligence in Cardiovascular Disease Prevention: Is it Ready for Prime Time?Current atherosclerosis reports · 2024Review
- Polygenic Risk Score for Cardiovascular Diseases in Artificial Intelligence Paradigm: A Review.Journal of Korean medical science · 2023Review
- Identification of candidate biomarkers and mechanisms in foam cell formation from heterogeneous cellular origins via integrated transcriptome analysis.Annals of translational medicine · 2023Article
- Wearable Devices in Cardiovascular Medicine.Circulation research · 2023Review
- GENERATOR HEART FAILURE DataMart: An integrated framework for heart failure research.Frontiers in cardiovascular medicine · 2023Article
- A Review of Recent Advances in Vital Signals Monitoring of Sports and Health via Flexible Wearable Sensors.Sensors (Basel, Switzerland) · 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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiological disorders contribute to a significant portion of the global burden of disease. Cardiology can benefit from Big Data, which are generated and released by different sources and channels, like epidemiological surveys, national registries, electronic clinical records, claims-based databases (epidemiological Big Data), wet-lab, and next-generation sequencing (molecular Big Data), smartphones, smartwatches, and other mobile devices, sensors and wearable technologies, imaging techniques (computational Big Data), non-conventional data streams such as social networks, and web queries (digital Big Data), among others. Big Data is increasingly having a more and more relevant role, being highly ubiquitous and pervasive in contemporary society and paving the way for new, unprecedented perspectives in biomedicine, including cardiology. Big Data can be a real paradigm shift that revolutionizes cardiological practice and clinical research. However, some methodological issues should be properly addressed (like recording and association biases) and some ethical issues should be considered (such as privacy). Therefore, further research in the field is warranted.
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.