PRIZM: Cardiac Structure and Function Data from Larval Zebrafish

Figshare hosts a 792.8 MB repository supporting the PRIZM deep learning framework for automated cardiac phenotyping. The repository includes trained models, image-annotation pairs for training, test datasets, and derived analysis outputs, all released under a CC-BY-4.0 license by author Inho Kim. It was last updated on 2026-05-13.

Use Cases

• Benchmarking cardiac phenotyping algorithms based on provided test image datasets.
• Training new deep learning models for biomedical imaging using the supplied image-annotation pairs.
• Reproducing cardiac analysis outputs for validation studies based on the PRIZM-derived results.
• Conducting toxicological assessments of cardiovascular effects using automated phenotypic profiling.

Strengths

• Includes a trained deep learning model (PRIZM) ready for application.
• Provides image-annotation pairs explicitly for model training and test datasets for evaluation.
• Repository size is 792.8 MB, indicating substantial supporting resources.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale analyses.

Provenance

Source

figshare

Collection Method

Associated with the research study 'PRIZM: deep phenotypic profiling of cardiac structure and function in larval zebrafish'.

Freshness

Last updated 2026-05-13 09:11:27; freshness should be verified.