ArticleFrontiers in cellular neuroscience2022
A novel automated morphological analysis of Iba1+ microglia using a deep learning assisted model.
Article in Frontiers in cellular neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Dexmedetomidine inhibits microglia activation, neuroinflammation, and glycolysis in postoperative cognitive dysfunction by promoting YTHDF2-mediated PKM2 mRNA degradation.Molecular and cellular biochemistry · 2026Article
- Development of convolutional neural networks for automated brain-wide histopathological analysis in mouse models of synucleinopathies.NPJ Parkinson's disease · 2025Article
- Comparing non-machine learning vs. machine learning methods for Ki67 scoring in gastrointestinal neuroendocrine tumors.Scientific reports · 2025Article
- StainAI: quantitative mapping of stained microglia and insights into brain-wide neuroinflammation and therapeutic effects in cardiac arrest.Communications biology · 2025Article
- Unraveling microglial spatial organization in the developing human brain with DeepCellMap, a deep learning approach coupled with spatial statistics.Nature communications · 2025Article
- Chronic urinary tract infections cause persistent microglial changes in a humanized ɑ-synuclein mouse model.Journal of Parkinson's disease · 2024Article
- Heterozygous loss of Engrailed-1 and α-synucleinopathy (En1/SYN): A dual-hit preclinical mouse model of Parkinson's disease, analyzed with artificial intelligence.Neurobiology of disease · 2024Article
- Targeted therapy and deep learning insights into microglia modulation for spinal cord injury.Materials today. Bio · 2024Article
- A deep convolutional neural network for efficient microglia detection.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
There is growing evidence for the key role of microglial functional state in brain pathophysiology. Consequently, there is a need for efficient automated methods to measure the morphological changes distinctive of microglia functional states in research settings. Currently, many commonly used automated methods can be subject to sample representation bias, time consuming imaging, specific hardware requirements and difficulty in maintaining an accurate comparison across research environments. To overcome these issues, we use commercially available deep learning tools Aiforia
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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.