aceA Combined Deep Learning Approach to Screen Patients for Neuromuscular Pathology
Neuromuscular diseases (NMD), comprising over 600 different conditions, severely impact nerve and/or muscle function and lead to significant morbidity. Ultrasound is a non-invasive tool that is gaining acceptance for diagnosing NMD. In clinical practice, muscle ultrasound can be evaluated quantitatively or visually using an ordinal four-point grading score (Heckmatt score). Its current application is limited by time investment in manual analysis and lack of result transferability to other centers. Here, we prese…
A multi-modal deep learning framework using Heckmatt scores from six key muscles improved speed and diagnostic performance for muscle ultrasound, predicting neuromuscular pathology with an area under the precision-recall curve of 0.87 on a test set of 320 patients.
Findings come from a single-center framework, limiting transferability to other centers, and patient-specific BMI and age did not improve performance.
Evidence
- Peer-reviewedUltrasound in Medicine & Biology2026-08-15
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Truvace Impact Record TRV-2026-0799, v1: “A Combined Deep Learning Approach to Screen Patients for Neuromuscular Pathology.” Truvace, 2026-08-17. /record/TRV-2026-0799 (accessed at citation time). sha256 ae5d509455786d1f…
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