ArticleJournal fur Urologie und Urogynakologie : Zeitschrift fur Urologie und Urogynakologie in Klinik und Praxis2021
[What can machines do?]
Article in Journal fur Urologie und Urogynakologie : Zeitschrift fur Urologie und Urogynakologie in Klinik und Praxis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Use of Artificial Intelligence Methods for Improved Diagnosis of Urinary Tract Infections and Urinary Stone Disease.Journal of clinical medicine · 2025Review
- Does the Information Quality of ChatGPT Meet the Requirements of Orthopedics and Trauma Surgery?Cureus · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With increasing computing and storage capacity, the application of big data and artificial intelligence (AI) is almost inexorably finding its way into medicine. The main areas of application so far have been in radiology and pathology, as well as in other areas such as genome sequencing and psychiatry. By evaluating ever larger amounts of data, patterns are sought that can make physicians' work easier by making a preselection. In addition, efforts are being made to uncover previously unrecognized connections. Large amounts of data are recorded by the patients themselves using so-called wearables. How can this data be used meaningfully? What are the dangers? Efforts are also being made in urology to improve the treatment of urinary tract infections and kidney stones, for example, through the use of networked computer systems. Great progress can be expected in the next few years in the field of big data and AI. An enormous expansion of the areas of application is going to come; as such, we are only at the beginning of the development.
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.