ReviewBriefings in bioinformatics2023
From data to diagnosis: how machine learning is revolutionizing biomarker discovery in idiopathic inflammatory myopathies.
Review in Briefings in bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 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
12 citing papers in PubMed, 18 citations in OpenAlex.
- Global landscape of juvenile dermatomyositis research: a bibliometric analysis.Pediatric research · 2026Article
- A fusion-based multiomics classification approach for enhanced gene discovery in non-small cell lung cancer.Bioinformatics advances · 2026Article
- Autoimmune Neuromuscular Disorders at a Molecular Crossroad: Linking Pathogenesis to Targeted Immunotherapy.International journal of molecular sciences · 2025Review
- Smart Microbiomes: How AI Is Revolutionizing Personalized Medicine.Bioengineering (Basel, Switzerland) · 2025Review
- Idiopathic Inflammatory Myopathy-Molecular Mechanisms Underlying Its Pathogenesis and Physical Therapy Effects.International journal of molecular sciences · 2025Review
- Leucine-rich alpha-2 glycoprotein for detecting small bowel lesions in Crohn's disease: A critical review and the path forward.World journal of gastrointestinal endoscopy · 2025Article
- Health effects of intermittent fasting and the role of artificial intelligence technologies in optimizing its clinical translation.AIMS public health · 2025Review
- Discovery of urinary biosignatures for tuberculosis and nontuberculous mycobacteria classification using metabolomics and machine learning.Scientific reports · 2024Article
- From machine learning to clinical practice: phenotypic clusters of anti-MDA5 antibody-positive dermatomyositis.Briefings in bioinformatics · 2024Article
- Balancing Clinical Applicability and Scientific Depth in ML Models for MDA5-DM Prognosis.Briefings in bioinformatics · 2024Article
- Prediction Models Using Decision Tree and Logistic Regression Method for Predicting Hospital Revisits in Peritoneal Dialysis Patients.Diagnostics (Basel, Switzerland) · 2024Article
- Sporadic Inclusion Body Myositis at the Crossroads between Muscle Degeneration, Inflammation, and Aging.International journal of molecular sciences · 2024Review
Corrections and comments
- Commented on by
- Erratum issued
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Idiopathic inflammatory myopathies (IIMs) are a heterogeneous group of muscle disorders including adult and juvenile dermatomyositis, polymyositis, immune-mediated necrotising myopathy and sporadic inclusion body myositis, all of which present with variable symptoms and disease progression. The identification of effective biomarkers for IIMs has been challenging due to the heterogeneity between IIMs and within IIM subgroups, but recent advances in machine learning (ML) techniques have shown promises in identifying novel biomarkers. This paper reviews recent studies on potential biomarkers for IIM and evaluates their clinical utility. We also explore how data analytic tools and ML algorithms have been used to identify biomarkers, highlighting their potential to advance our understanding and diagnosis of IIM and improve patient outcomes. Overall, ML techniques have great potential to revolutionize biomarker discovery in IIMs and lead to more effective diagnosis and treatment.
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.