ReviewHerz2022
[Future of interventional cardiology : Does everything revolve around AI and robotics?]
Review in Herz, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, software-assisted imaging systems, such as computed tomography, have contributed to the improvement of noninvasive options for the diagnostics of coronary heart disease (CHD). In addition, the possibilities of individual morphological and functional atherosclerotic plaque evaluation could be further refined, e.g. by the use of optical coherence tomography or the quantitative flow ratio (QFR). Due to the development of robotic-assisted catheter systems, it has been possible to make coronary interventions more precise and with less radiation exposure for the examiner. It is to be expected that in the future even better algorithms will be developed by the analysis of very large amounts of data. These will enable a more exact, dynamic and personalized prediction of, e.g. treatment success or individual risk profiles, in order to positively and sustainably influence the treatment of patients with cardiovascular diseases.
Indexed as
Identifiers
36305916What 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.