Machine intelligence in the OR: optimizing the effectiveness of surgeons with IT tools

Machine intelligence in the OR: optimizing the effectiveness of surgeons with IT toolsHeinz U. Lemke, International Foundation for Computer Assisted Radiology and Surgery (IFCARS)

Medicine is undergoing a historic transition, moving away from a trial-and-error model of care, towards individualized treatment strategies based on patient-specific knowledge management of disease and...

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Medicine is undergoing a historic transition, moving away from a trial-and-error model of care, towards individualized treatment strategies based on patient-specific knowledge management of disease and treatment. Not only the biomedical systems sciences and engineering, mathematics, medical imaging and medical informatics but also the discipline of machine intelligence and in a wider sense computer assisted radiology and surgery (CARS) are enablers of this new paradigm. With an appropriate ICT platform, for example, medical workstations for domain-specific applications, they provide the methods and tools for knowledge management and specifically for a patient-specific medicine.

 

Important aspects of these dramatically evolving and ICT based methodologies and tools are possibilities for:

  1. Modelling of human organ systems, pathologies and clinical processes from scientifically based evidence, medical guidelines and data mining.
  2. Analysis (e.g. inferencing) and adaptation (e.g. domain-specific learning) of models from data and information gathered from specific patients through imaging and biosensors in order to generate knowledge models of patient-specific situations to improve accuracy of diagnosis and appropriateness of treatment processes.
  3. Higher quality of therapeutic interventions by means of real time integration of information in patient-specific models and therapeutic processes through computer assisted workflow, knowledge and decision management


With an appropriate employment of these methods and tools, they become enablers of intelligent infrastructures and processes in medical diagnosis and therapy, hopefully making complex situations and processes in healthcare more comprehensible, visible, reproducible, transparent and understandable for the human, i.e. for the physician and patient......

 

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