ArticleDigestive diseases and sciences2024
Gastroenterology Fellowship and Postdoctoral Training in Omics and Statistics-Part II: How Can It Be Achieved?
Article in Digestive diseases and sciences, 2024. 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
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Authors and funding
6 authors.
Funding
Abstract
Data are being generated, collected, and aggregated in massive quantities at exponentially increasing rates. This "big data," discussed in depth in the first section of this two-part series, is increasingly important to understand the nuances of the gastrointestinal tract and its complex interactions and networks involving a host of other organ systems and microbes. Creating and using these datasets correctly requires comprehensive training; however, current instruction in the integration, analysis, and interpretation of big data appears to lag far behind data acquisition. While opportunities exist for those interested in acquiring the requisite training, these appear to be underutilized, in part due to widespread ignorance of their existence. Here, to address these gaps in knowledge, we highlight existing big data learning opportunities and propose innovative approaches to attain such training. We offer suggestions at both the undergraduate and graduate medical education levels for prospective clinical and basic investigators. Lastly, we categorize training opportunities that can be selected to fit specific needs and timeframes.
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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.