ArticleAnnals of medicine and surgery (2012)2025
AI-powered CT imaging for early detection of subclinical pulmonary fibrosis in antisynthetase syndrome: a new era in autoimmune lung diagnostics.
Article in Annals of medicine and surgery (2012), 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
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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
1 citing paper in PubMed.
- Beyond CT and MRI: terahertz imaging as a frontier tool for early mesothelioma diagnosis.Annals of medicine and surgery (2012) · 2025Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Antisynthetase syndrome (ASS), a rare autoimmune condition, often leads to subclinical pulmonary fibrosis (PF) that remains undetected until irreversible damage occurs. High-resolution computed tomography (HRCT) is pivotal in early PF detection, yet interpretation inconsistencies remain a challenge. Artificial intelligence (AI) and machine learning (ML) applications-such as multiple feature texture analysis, CALIPER, and deep learning segmentation tools-are revolutionizing lung imaging by minimizing observer variability, enhancing early diagnosis, and uncovering novel imaging biomarkers. While promising, the adoption of AI for rare disease diagnostics like ASS requires overcoming data limitations, bias, and validation hurdles. This letter calls for integrated genomic-imaging models, open-access repositories, and international data collaboration to effectively translate AI advancements into routine diagnostics for autoimmune lung disease.
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Registered trials
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