ReviewNature methods2025
MIFA: Metadata, Incentives, Formats and Accessibility guidelines to improve the reuse of AI datasets for bioimage analysis.
Review in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- The missing data for intelligent scientific instruments.Nature methods · 2026Article
- SAMJ: fast image annotation on ImageJ/Fiji via segment anything model.Nature communications · 2026Article
- Bridging annotated microscopy imaging data and analysis method development for scientific discovery.Patterns (New York, N.Y.) · 2026Review
- Following a cell's every move.Nature methods · 2025Article
- Making the most of bioimaging data through interdisciplinary interactions.Journal of cell science · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
28 authors.
Funding
Abstract
Artificial intelligence (AI) methods are powerful tools for biological image analysis and processing. High-quality annotated images are key to training and developing new algorithms, but access to such data is often hindered by the lack of standards for sharing datasets. We discuss the barriers to sharing annotated image datasets and suggest specific guidelines to improve the reuse of bioimages and annotations for AI applications. These include standards on data formats, metadata, data presentation and sharing, and incentives to generate new datasets. We are sure that the Metadata, Incentives, Formats and Accessibility (MIFA) recommendations will accelerate the development of AI tools for bioimage analysis by facilitating access to high-quality training and benchmarking data.
Indexed as
Identifiers
40954297What 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.