ReviewCirculation research2018
Biomedical Informatics on the Cloud: A Treasure Hunt for Advancing Cardiovascular Medicine.
Review in Circulation research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Comparing extraction method efficiency for high-throughput palaeoproteomic bone species identification.Scientific reports · 2023Article
- Building Trust in Medical Use of Artificial Intelligence - The Swarm Learning Principle.Journal of CME · 2023Article
- Environmental exposure as a risk-modifying factor in liver diseases: Knowns and unknowns.Acta pharmaceutica Sinica. B · 2021Review
- Mobile 5P-Medicine Approach for Cardiovascular Patients.Sensors (Basel, Switzerland) · 2021Article
- Orchestrating privacy-protected big data analyses of data from different resources with R and DataSHIELD.PLoS computational biology · 2021Article
- Article
- Data Integration Challenges for Machine Learning in Precision Medicine.Frontiers in medicine · 2021Review
- Cardioinformatics: the nexus of bioinformatics and precision cardiology.Briefings in bioinformatics · 2020Article
- The Oxford Royal College of General Practitioners Clinical Informatics Digital Hub: Protocol to Develop Extended COVID-19 Surveillance and Trial Platforms.JMIR public health and surveillance · 2020Article
- Frontiers in Vascular Physiology Grand Challenges in Vascular Physiology.Frontiers in physiology · 2020Article
- Review
- Omics, Big Data, and Precision Medicine in Cardiovascular Sciences.Circulation research · 2018Article
- Embedded deep learning in ophthalmology: making ophthalmic imaging smarter.Therapeutic advances in ophthalmologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
In the digital age of cardiovascular medicine, the rate of biomedical discovery can be greatly accelerated by the guidance and resources required to unearth potential collections of knowledge. A unified computational platform leverages metadata to not only provide direction but also empower researchers to mine a wealth of biomedical information and forge novel mechanistic insights. This review takes the opportunity to present an overview of the cloud-based computational environment, including the functional roles of metadata, the architecture schema of indexing and search, and the practical scenarios of machine learning-supported molecular signature extraction. By introducing several established resources and state-of-the-art workflows, we share with our readers a broadly defined informatics framework to phenotype cardiovascular health and disease.
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.