AI-based predictive biomarkers for chronic neurological diseases: the rAIdD prospective, multicenter, observational study protocol - Summary - MDSpire

Predictive Biomarkers Utilizing AI for Chronic Neurological Disorders: Protocol for the rAIdD Multicenter Observational Study

  • By

  • Simone Varrasi

  • Alfredo Pulvirenti

  • Vincenzo Catania

  • Maurizio Palesi

  • Concetto Spampinato

  • Davide Patti

  • Orazio Tomarchio

  • Giovanni Micale

  • Alessia Simone

  • Lisa Passarello

  • Federica Proietto Salanitri

  • Giovanni Patanè

  • Salvatore Ravidà

  • Clara Grazia Chisari

  • Giuseppe Zappalà

  • Emanuele D'Amico

  • Carlo Avolio

  • Federica Felicetti

  • Claudio Gasperini

  • Simone Rossi

  • Paolo Manganotti

  • Pierpaolo Busan

  • Carmelo Rodolico

  • Rossella Laudani

  • Roberto Marino

  • Massimo Villari

  • Francesco Patti

  • July 17, 2026

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Objective:

To develop an interoperable digital infrastructure for early diagnosis, monitoring, and risk stratification in chronic neurological diseases using AI and multimodal data.

Approach:
  • Data Collection: Participants will undergo standardized clinical, neuropsychological, neuroimaging, and digital assessments at baseline and follow-ups (6, 12, 18 months), including disease-specific disability scales, mood assessments, and lifestyle profiling.
Key Findings:
  • Chronic neurological disorders share multifactorial pathophysiological mechanisms.
  • Wearable technologies and AI can enhance personalized disease management.
  • The study aims to identify shared mechanisms and predictive biomarkers across MS, PD, and AD.
Interpretation:

The rAIdD project seeks to leverage AI and digital technologies to improve the understanding and management of chronic neurological disorders.

Limitations:
  • The study is limited to Italian academic and clinical centers, which may affect generalizability.
  • The reliance on self-reported data may introduce bias.
Conclusion:

The rAIdD initiative represents a significant step towards integrating AI and digital health technologies in the management of chronic neurological diseases.

Original Source(s)

AI-based predictive biomarkers for chronic neurological diseases: the rAIdD prospective, multicenter, observational study protocol

  • by Simone Varrasi, Alfredo Pulvirenti, Vincenzo Catania, Maurizio Palesi, Concetto Spampinato, Davide Patti, Orazio Tomarchio, Giovanni Micale, Alessia Simone, Lisa Passarello, Federica Proietto Salanitri, Giovanni Patanè, Salvatore Ravidà, Clara Grazia Chisari, Giuseppe Zappalà, Emanuele D'Amico, Carlo Avolio, Federica Felicetti, Claudio Gasperini, Simone Rossi, Paolo Manganotti, Pierpaolo Busan, Carmelo Rodolico, Rossella Laudani, Roberto Marino, Massimo Villari, Francesco Patti

  • July 17, 2026

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