The present study involves the collection of clinical data, from muscle MRI (on clinical indication), muscle biopsy (on clinical indication) and DNA analysis. For each participating subject, the samples, collected with standardized methodologies, will be analyzed with the most sophisticated and advanced artificial intelligence computational techniques which will integrate them to try to obtain a pattern of information that will allow the patient to be classified as precisely as possible into correlation both to the clinical evaluation and to genomic data (i.e. from DNA analysis), muscle magnetic resonance imaging (MRI), and related to muscle biopsy. The aim is to create a new generation of “precision diagnosis” tools that allow researchers and/or healthcare professionals to group patients with inherited neuromuscular diseases based on multiple data points. This would give the possibility, by identifying the peculiar characteristics of the various groups of patients, to precisely follow the individual patient over time, thus also collecting information that will be used to understand how the different clinical conditions linked to the different groups can evolve over time. Furthermore, this type of study can give new perspectives to the knowledge of the pathogenetic and transmission mechanisms of hereditary neuromuscular diseases, increasing the possibility that effective therapies can be found for patients grouped according to this classification. To this end, the data collected from you will be analyzed through the application of computational methods based on artificial intelligence which allow the creation of solutions focused on the integration of health data to support patients, healthcare workers and citizens.