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. 2025 Jun;44(2):62-66.
doi: 10.36185/2532-1900-927.

Empowering clinicians with artificial intelligence in hereditary neuromuscular disorders

Andi Nuredini  1 , Marco Savarese  2 , Filippo Maria Santorelli  3 , Rossella Ginevra Tupler  1
Affiliations

Empowering clinicians with artificial intelligence in hereditary neuromuscular disorders

Andi Nuredini et al. Acta Myol. 2025 Jun.

Abstract

Artificial Intelligence (AI) is the ability of machines to perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making. Its integration into healthcare may revolutionize many areas of medicine, including the diagnosis and management of neuromuscular disorders (NMDs).

These disorders, characterized by their clinical and genetical complexity and heterogeneity, demand innovative approaches to improve patient outcomes. Among these approaches, AI-driven solutions hold immense potential. However, the success of these solutions depends on preparing a new generation of clinicians equipped to harness the multifaceted power of AI.

One remarkable initiative addressing this need is the CoMPaSS-NMD project, which pioneers an interdisciplinary framework for developing AI-driven strategies to stratify patients using multiple clinical, histopathological, MRI e genetic datasets. By fostering a shared working language and integrating diverse competencies, the project aims to advance knowledge dissemination and bridge gaps between traditional disciplines. This approach is vital for addressing the challenges posed by NMDs, where early diagnosis and personalized treatment plans are critical.

To support this mission, the Young Investigator Training (YIT) initiative within CoMPaSS-NMD fosters education and scientific exchange among early-career researchers. By promoting high-quality clinical assessments and multidisciplinary training, YIT prepares a new generation to meet the evolving challenges in NMD care and research.

Keywords: MRI; artificial intelligence; genetics; histology; neuromuscular disorders.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1.
Figure 1.
Overall program of the first CoMPaSS-NMD Autumn School.
Figure 2.
Figure 2.
Photo of the participants to the first CoMPaSS-NMD Autumn School.
Figure 3.
Figure 3.
Word cloud with the most reported words from the CoMPaSS-NMD Autumn School participants.
See this image and copyright information in PMC

References

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