ArticleCell reports. Medicine2023
Integration of deep learning-based histopathology and transcriptomics reveals key genes associated with fibrogenesis in patients with advanced NASH.
Article in Cell reports. Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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
10 citing papers in PubMed, 16 citations in OpenAlex.
- Applications of Artificial Intelligence and Smart Devices in Metabolic Dysfunction-associated Steatotic Liver Disease.Journal of clinical and translational hepatology · 2026Article
- Digital pathology and spatial omics in steatohepatitis: Clinical applications and discovery potentials.Hepatology (Baltimore, Md.) · 2025Review
- Complexity of metabolic dysfunction-associated steatotic liver disease: State of the art review.Journal of the Chinese Medical Association : JCMA · 2025Review
- Review
- Review
- AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseases.Nature medicine · 2024Article
- Spatial genomics: mapping human steatotic liver disease.Nature reviews. Gastroenterology & hepatology · 2024Review
- Review
- Cross-attention enables deep learning on limited omics-imaging-clinical data of 130 lung cancer patients.Cell reports methods · 2024Article
- A data-driven approach to decode metabolic dysfunction-associated steatotic liver disease.Annals of hepatologyReview
Corrections and comments
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Authors and funding
15 authors at 3 institutions in 1 country.
Funding
Abstract
Nonalcoholic steatohepatitis (NASH) is the most common chronic liver disease globally and a leading cause for liver transplantation in the US. Its pathogenesis remains imprecisely defined. We combined two high-resolution modalities to tissue samples from NASH clinical trials, machine learning (ML)-based quantification of histological features and transcriptomics, to identify genes that are associated with disease progression and clinical events. A histopathology-driven 5-gene expression signature predicted disease progression and clinical events in patients with NASH with F3 (pre-cirrhotic) and F4 (cirrhotic) fibrosis. Notably, the Notch signaling pathway and genes implicated in liver-related diseases were enriched in this expression signature. In a validation cohort where pharmacologic intervention improved disease histology, multiple Notch signaling components were suppressed.
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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.