ReviewBiophysical journal2025
Integrative functional optical imaging approaches: Optics, microfluidics, and machine learning for neuroscience in organoids and small-animal models.
Review in Biophysical journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Organoids for disease modeling and treatment: state-of-the-art.Experimental hematology & oncology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Advances in functional imaging have transformed neuroscience, enabling real-time mapping of neural activity and cellular dynamics. Techniques such as light-sheet microscopy allow whole-brain recordings in model organisms like Caenorhabditis elegans and zebrafish, revealing mechanisms of sensorimotor processing, learning, and neural circuit formation. More recently, the vast complexity of these datasets necessitates machine-learning tools for efficient analysis. Machine-learning-driven approaches improve data quality through denoising, automate segmentation of neurons and tissues, and enable analyses on complex data. By integrating machine learning with advanced imaging, researchers can decode developmental trajectories and neural-network function with unprecedented precision. This review explores the synergy between imaging and computation, highlighting how these innovations drive discoveries in neuroscience.
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.