Evidence map›Paper›PMID 40970141›Full record

ReviewFrontiers in digital health2025

How the world of biobanking is changing with artificial intelligence.

Michaela Th Mayrhofer

Abstract readReview
In one paragraph

Review in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Michaela Th MayrhoferInstitute of Human Genetics, Medical University of Innsbruck, Innsbruck, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial Intelligence is increasingly shaping the practice of biobanking by influencing how biobanks evolve and operate, especially when it concerns their relationship to data. By assessing four key parameters-size, site, speed, and access-this paper analyzes the impact of AI technologies on biobanks, presenting them as dynamic boundary objects that produce biovalue by transforming biological material and data into intangible assets of the data-driven bioeconomy. Historically rooted at the intersection of health research and healthcare, biobanking is continually reshaped by emerging technologies, policies, and societal expectations. While biobanks were originally defined as collections of samples and associated data, they have recently evolved into complex infrastructures for both data and samples.

Indexed as

accessartificial intelligencebiobankdataficationhealth economysitesizespeed

Identifiers

PMID40970141
PMCPMC12440935

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.