Expert Systems (ES) can provide an alternative methodology in analysing data to identify variables with the highest correlation to the outcome using the most appropriate data analysis and algorithms. By applying their effective machine learning (ML) abilities, significant research time and costs can be saved. The study aims to systematically review the applications of ES in neurological research and their methodological models for effective multi-variate analysis. Their domains, development and validity will be identified on WP6. The ES is tested for accuracy, feasibility, and acceptability in real-world practice. Artificial Intelligence (AI) knowledge-based system for data analysis and interpretation includes an algorithm and software to emulate human cognitive functions in the analysis, interpretation, and comprehension of heterogenous data. Data analytics according to the definitions of previous WPs and especially WP4 include visualisation, query definition and multi-purpose analytics. Interactive and intuitive visualisations (dashboards) assist clinicians to develop actionable insights about patients’ health condition and take the necessary corrective actions. The present deliverable provides the basic structure of the algorithm that includes all variables that have been identified and result in the creation of the basic structure that hosts the data analysis. The system can receive a variety of variables analysed through AI algorithm and provide the end users with the appropriate results.