Mission Summary

ES, version 2022-01-09 /

• Medical Decisions Support:
  • Make knowledge better available for decisions. Strategies for differential diagnosis and evaluation of considered treatments.
• AI as "Assisted Intelligence":
  • Helping but not replacing healthcare professionals.
  • A task oriented approach, identifying problems and seeking solutions.
  • Make healthcare AI more friendly and more transparent, with explanations of the decision process.
  • Motivations in the scope of the evolution of medical informatics.
    
• Multiple factors:
  • Decisions taking account of many factors presented as graphs, with the relative weights of relationships between concepts. This require the management of complex medical information in a N-dimentional space, by means of graph technologies. Therefore both medical knowledge and patient records need to be converted in graphs.
• Human Interface:
  • Development of easy and interactive interfaces between the graphs in human minds, i.e. neurons and synapses, and the graphs in computers.
• Knowledge:
  • Better access to already existing medical knowledge. A large amount of biomedical knowledge is in principle already available but the question is now how to use this knowledge in a more efficient way.
    
  • Maintenance of a synthesis of agreed current medical knowledge. Conversion of the current state of the arts into graphs.
• Community:
  • A multidisciplinary community including healthcare professionals, data scientists, software developers and students.
  • Role:
  • Scientific: dealing with methodology and knowledge base, supported by universities and public grants.
  • Operators: dealing with installations and sustainability, supported by the users.
  • Care provider: in contact with the patient and taking the final decision.
• Openeness:
  • International Open Source and Open Data collaborations as a not-for-profit initiative, With support from scientific communities, universities and seeking grants of common interest. An exiting  challenge.
  • Intended to support operators of services to users in practice, but in a non exclusive way. Business activities of operation of services to end users, as installation, training and maintenance.
  • Transparency of the sources of information by accredited authors.
• Research:
  • Research in order to improve the graph knowledge base, particularly about the quantification of the relationships between concepts.
  • Learning from the follow-up of the recommendations.
• Road map:
  • Incremental development: start with exercises on simple decision schema and make improvements step by step. Prototypes as proof of concept focusing on methodology and interdependence of any medical specialities.
• Intended users:
  • Telemedicine in situations where there is limited local qualifications and/or not enough time per patient.
  • Many specialized health organizations are working on knowledge bases in traditional and incompatible ways.  The challenges  are integration and accessibility in a format suited for decision support.
  • Quality checks which may provide warnings.
  • Contribution to medical education and training, in front of interactive decision strategies.