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In this manuscript we report an evaluation of the reliability of clinical research rules creation by multiple clinicians using the Health Archetype Language (HAL-42) and user interface.
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Tips are given for effective rule creation, as well as for rule precision and performance.
If you follow traditional task or rule creation flows, you assign things to logical arguments via their unique ID.
Using a case study approach, we found that how employees' were engaged in the rule creation process led to different levels of psychological ownership, and this, in turn, led to different levels of rule enactment.
Our system is based on multi model architecture that allows for adaptative rule creation and algorithm effectiveness evaluation, focused on the automatic control of hypertension in the intensive care unit.
Because students make the rules at Sudbury Valley and have responsibility for enforcing them, they have far more respect for the rules than do students in a standard school who have little or no voice in rule creation or enforcement (for further elaboration, see Gray 2010c).
The Manual rule creation section outlines our manual rule creation process.
The rule creation algorithm is applied to multiple datasets, both with and without prior filtering to discover significant variables.
To design 'negative' rules (i.e. rules that determine that an instance has no relation), we employ the same data-driven procedure that was used to design the relation classification rules (see the Manual rule creation section).
As positive rules (i.e. rules that determine that an instance has a relation), we simply use all the rules that we hand-crafted for relation classification in the Manual rule creation section.
The BitCoin model is attractive, with disaggregated rules around creation and exchange, and with no one company in control, no one person can profit from virtual "over-printing".
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