  Alzheimer's Disease is a global health challenge that requires early and
accurate detection to improve patient outcomes. Magnetic Resonance Imaging
(MRI) holds significant diagnostic potential, but its effective analysis
remains a formidable task. This study introduces a groundbreaking decentralized
expert system that cleverly combines blockchain technology with Artificial
Intelligence (AI) to integrate robust anomaly detection for patient-submitted
data.
  Traditional diagnostic methods often lead to delayed and imprecise
predictions, especially in the early stages of the disease. Centralized data
repositories struggle to manage the immense volumes of MRI data, and persistent
privacy concerns hinder collaborative efforts. Our innovative solution
harnesses decentralization to protect data integrity and patient privacy,
facilitated by blockchain technology. It not only emphasizes AI-driven MRI
analysis but also incorporates a sophisticated data anomaly detection
architecture. These mechanisms scrutinize patient-contributed data for various
issues, including data quality problems and atypical findings within MRI
images.
  Conducting an exhaustive check of MRI image correctness and quality directly
on the blockchain is impractical due to computational complexity and cost
constraints. Typically, such checks are performed off-chain, and the blockchain
securely records the results. This comprehensive approach empowers our
decentralized app to provide more precise early-stage Alzheimer's Disease
predictions. By merging the strengths of blockchain, AI, and anomaly detection,
our system represents a pioneering step towards revolutionizing disease
diagnostics.
