ArticleScientific reports2025
Development of an artificial intelligence powered software for automated analysis of skeletal muscle ultrasonography.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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.
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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.
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Who cites it
8 citing papers in PubMed.
- Muscle Ultrasound Is a Sensitive Outcome Measure in ALS.Muscle & nerve · 2026Observational
- Assessing the reliability of interprofessional raters on peripheral muscle ultrasonography in pediatric oncology: A prospective observational study.Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition · 2026Observational
- Greedy regression-based cross-species gene expression modeling: a translational framework for forensic wound age estimation.International journal of legal medicine · 2026Article
- Artificial intelligence-driven assessment of sarcopenia in orthopedic geriatrics: technical progress and clinical implications.Frontiers in endocrinology · 2026Review
- Bridging assessment, biomarkers, and interventions: progress in muscle health research.Frontiers in rehabilitation sciences · 2026Article
- Trajectories of Recovery after ACutE and cRitical illness (TRACER): a prospective observational study protocol.BMJ open · 2025Article
- Acute skeletal muscle wasting in patients with acute kidney injury requiring continuous kidney replacement therapy: A prospective multicenter study.Journal of critical care · 2025Observational
- Multimodal machine learning to predict response to ultrasound-guided botulinum and vibration therapy in muscle spasticity a clinical and imaging correlation study.Frontiers in bioengineering and biotechnology · 2025Article
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Authors and funding
12 authors.
Funding
Abstract
Muscle ultrasound has high utility in clinical practice and research; however, the main challenges are the training and time required for manual analysis to achieve objective quantification of muscle size and quality. We aimed to develop and validate a software tool powered by artificial intelligence (AI) by measuring its consistency and comparability of expert manual analysis quantifying lower limb muscle ultrasound images. Quadriceps complex (QC) and tibialis anterior (TA) muscle images of healthy, intensive care unit, and/or lung cancer participants were captured with portable devices. Manual analyses of muscle size and quality were performed by experienced physiotherapists taking approximately 24 h to analyze all 180 images, while automated analyses were performed using a custom-built deep-learning model (MyoVision-US), taking 247 s (saving time = 99.8%). Consistency between the manual and automated analyses was good to excellent for all QC (ICC = 0.85-0.99) and TA (ICC = 0.93-0.99) measurements, even for critically ill (ICC = 0.91-0.98) and lung cancer (ICC = 0.85-0.99) images. The comparability of MyoVision-US was moderate to strong for QC (adj. R
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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.