By Carlo Combi, Elpida Keravnou-Papailiou, Yuval Shahar
The potent and effective use of knowledge structures in healthiness care enterprises and providers is a crucial portion of the standard of existence world wide. The modeling of time has attracted curiosity from a couple of study groups, every one addressing facets from its particular sphere of pursuits. The database structures neighborhood is attracted to the best way to shop, keep, and question time-oriented information. the unreal Intelligence (AI) neighborhood is drawn to formal theories of time, temporal logics, temporal constraints and temporal reasoning strategies. the substitute Intelligence in drugs (AIM) group is drawn to the wider concerns occupied with reasoning approximately time-oriented facts: specifically, the results of temporal reasoning on scientific projects reminiscent of prognosis, tracking, and longitudinal guideline-based care.
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Extra info for Temporal Information Systems in Medicine
Projection is the task of computing the likely consequences of a set of conditions or actions, usually given as a set of causeeffect relations. , when we need to decide how the patient’s state will be after we administer to the patient a certain drug with known side effects). Forecasting involves predicting particular future values for various parameters given a vector of time-stamped past and present measured values, such as anticipating changes in future hemoglobin-level values, given the values up to and including the present.
One of the first proposals formally dealing with time granularity was made by Clifford , in which he provides a particularly clean view of a structure for temporal domains. Using a set-theoretic construction, Clifford defines a simple but powerful structure of time units. He assumes for every temporal domain a chronon. By the repeated operation of constructed intervallic partitioning intuitively equivalent to segmentation of the time line into mutually exclusive and exhaustive intervals (say, constructing 12 months from 365 days) - Clifford defines a temporal universe, which is a hierarchy of time levels and units.
Interpretation involves abstraction of a set of time-oriented patient data, either to an intermediate level of meaningful temporal patterns, as is common in the temporal-abstraction task or in the monitoring task, or to the level of a definite diagnosis or set of diagnoses that explain a set of findings and symptoms, as is common in the diagnosis task. Interpretation, unlike forecasting and projection, involves reasoning about only past and present data and not about the future. 3 Temporal Reasoning 19 From the methodological point of view, one general criterion that can be used when classifying temporal-reasoning research is whether it uses a deterministic or a probabilistic approach .