Multi-Expert Discovery of Personalized Optimal Biomedical Solutions (patent pending)


  • – AI-Driven Framework for Discovery of Multi-Expert Personalized Biomedical Models & Indicators
  • – High-Capacity Engine for Multi-Factor Simulation and Multi-Objective Optimization of Treatment, Wellness & Rehabilitation Strategies
  • – 24/7 Automated Personalization, Monitoring & Decision Support
  • – Optimal Combination of All Available Biomedical Resources, Novel Research Results & Personal Data to Solve Your Current Problems
  • – Clear Explanation & Interpretation of the Discovered Personalized Treatment and Wellness Strategies
  • – Early Detection of the Emerging Medical Abnormalities, Health-Critical & Acute Events, Overtraining and Psychological Conditions
  • – Predictive Indications of Personalized Zones of Optimal Performance in Sport and Other Competitive Fields



  • – Early Detection of Emerging Abnormalities or Overtraining from Wearable-Device Data
  • – Early Detection of Treatment Effects for Personalization of Treatment Strategy and Regimen
  • – Predictive Personalization by Matching Current Biomedical State to Existing Cases
  • – Predictive Alerts for Rare & Hard-to-Quantify Best-Performance or Critical States
  • – Discovery of Optimal Regimen from the Long History of Personal Data
  • – Discovery of Personalized Health-Critical Geo-Magnetic / Weather Events and Predictive Alerts
  • – Quantitative Description and Monitoring of Individual Zones of Optimal Functioning (IZOF) v
  • – Monitoring and early detection of emerging life-threatening abnormalities
  • – Integrated Decision Support Solutions for Athletes and Coaches
  • – Early Diagnostics and Monitoring of Emerging Neurological, Psychological, Psychotic, and Developmental Abnormalities from Wearable-Device (ECG and gait) and Multi-Modal Clinical Data
  • – Discovery of Optimal Personalized Protocols in Neurofeedback and Other Alternative Therapies
  • – Discovery of Optimal Nutraceutical or Drug Combinations
  • – Engine for forward simulation and multi-objective discovery of optimal wellness strategies:
  • – Uses all available data to quantify current psycho-physiological personal state
  • – Using analytical and deep generative models, creates multi-horizon scenario paths incorporating potential environment and weather effects, probability of genomic mutations, probability of developing different abnormalities given current state and other factors.
  • – Using simulation results, multi-objective optimization engine discovers complementary sets of optimal wellness-maintenance strategies
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