Data mining techniques and applications in medicine
Date Issued
1999
Author(s)
DOI
http://dx.doi.org/10.1016/S0933-3657(98)00061-X
Abstract
In his excellent article on ‘the adolescence of AI in Medicine’, Edward H.
Shortliffe (AIM, 1993, 5:93-106) exposes three factors that may influence the
successful integration of AI systems into patient-care settings: enhancement of
training, international standards, and information infrastructure. Since 1993, information
infrastructure has certainly advanced more than the other two factors.
Nowadays, modern hospitals and health care institutions are rapidly advancing
their information systems. What was previously an isolated data base or a laboratory
information system is now integrated in a larger scale (departmental, hospital,
or community-based) medical information system
Shortliffe (AIM, 1993, 5:93-106) exposes three factors that may influence the
successful integration of AI systems into patient-care settings: enhancement of
training, international standards, and information infrastructure. Since 1993, information
infrastructure has certainly advanced more than the other two factors.
Nowadays, modern hospitals and health care institutions are rapidly advancing
their information systems. What was previously an isolated data base or a laboratory
information system is now integrated in a larger scale (departmental, hospital,
or community-based) medical information system