ArticleLight, science & applications2022
Deep learning accelerates whole slide imaging for next-generation digital pathology applications.
Article in Light, science & applications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Cross-Domain Benchmarking of Focus Measures for Smear-Microscopy Autofocus Under a Consensus-Audited Reference.Journal of imaging · 2026Article
- Hybrid deep reconstruction for vignetting-free upconversion imaging through scattering in epsilon-near-zero materials.Light, science & applications · 2026Article
- AI-Driven Drug Discovery: Focus on Targets for Solid Tumors.Pharmaceutics · 2026Review
- Automated HER2 Scoring with Uncertainty Quantification Using Lensfree Holography and Deep Learning.BME frontiers · 2026Article
- BlurryScope enables compact, cost-effective scanning microscopy for HER2 scoring using deep learning on blurry images.NPJ digital medicine · 2025Article
- Pre-Implantation Bovine Embryo Evaluation-From Optics to Omics and Beyond.Animals : an open access journal from MDPI · 2023Review
- Digital staining facilitates biomedical microscopy.Frontiers in bioinformatics · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Deep learning demonstrates the ability to significantly increase the scanning speed of whole slide imaging in histology. This transformative solution can be used to further accelerate the adoption of digital pathology.
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.