Abstract: A diagnostic enactive medical system that guides a user during acquisition and analyses of medical data for diagnosis and risk assessment. A method of using data-centric analysis and interpretation of acquired medical data in conjunction with metadata management in the point-of-care enactive medical system transforms raw medical data to generate feature-sets of a small number of closely related features associated with a particular medical or physiological state. Medical data from the point-of-care enactive medical system converges onto one or more feature-sets, interacts with the user to provide commentary or request additional information or data concerning a patient. Using an expert knowledgebase, the point-of-care enactive medical system learns from the medical data and then provides the user of tasks suitable for dynamic construction of point-of-care enactive medical knowledge, diagnoses, and recommendations for risk and/or treatment.
This disclosure relates generally to an application of complexity science and expert knowledge to analyses of medical data for evaluation of risk for emergent diseases and diagnoses. More particularly, an enactive point-of-care medical system and method is disclosed. There is an efferent-afferent relationship between a medical system and a user, such that the system includes a learning component such that the system learns from the user and the data acquisition device as to incorporate relevant data and/or transformed data into a feature and/or feature-set of a physiological condition such that this knowledge is incorporated into and/or added to the knowledgebase.