Integrating Kernel Methods Into a Knowledge-based Approach to Evidence-based Medicine

Introduction An abundance of information is generated during the process of critical care. Much of this information can now be captured and stored using clinical information systems (CIS) that have become commercially available for use in intensive care over the last years. These systems provide for a complete medical documentation at the bedside and their clinical usefulness and efficiency has been shown repeatedly [6, 7, 11]. While databases with more than 2,000 separate patient-related variables are now available for further analysis [8], the multitude of variables presented at the bedside even without a CIS precludes medical judgement by humans. A physician may be confronted with more than 200 variables in the critically ill during a typical morning round [21]. We know, however, that even an experienced physician is often not able to develop a systematic response to any problem involving more than seven variables [18]. Moreover, humans are limited in their ability to estimate th