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The following code snippet shows the use of the DROP TABLE command to delete the tempTransaction table:

This information can be used to judge the effectiveness of differing diagnoses, treatment, and care options, as well as an individual doctor s performance Data mining this information can help to increase the quality of care by establishing medical practices that result in improved care, such as decreasing mortality rates When preparing data for this purpose, care should be taken to ensure any bias in patient populations within speci c facilities is taken into account by normalizing the data based on a model of patient risk Models can also be built from this data that take into account information on the patients, such as demographic data, to make predictions of the type of care that leads to the best outcome for an individual patient.

2 2 (x x )(y y ) y y x x 1 exp 2 xy + 2(1 2 ) x x y y xy

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Improving diagnosis: Early diagnosis of problems or identi cation of potential long-term side effects can positively impact the patient and can result in signi cantly lower costs Methods such as decision trees are often built from the historical clinical data, including the patient s symptoms, health history, and demographics, to predict future issues, and provide an opportunity for intervention Data collected is often noisy, with many missing values, and needs to be cleaned before building any models This cleaning may also need to take into account standardization of the vocabulary used and the incorporation of concept hierarchies to map many terms into a more standardized list Coupling historical diagnosis data with information generated at a genetic level, such as gene expression data, is now starting to be used to enhance diagnosis and enable more personalized medicine.

The next example uses a range reference in a named formula. Figure 3-18 shows the Define Name dialog box when defining the following named formula (named Total).

Allocating resources: Data mining is also being used to optimize the operational ef ciency of hospitals Models are built to make predictions of demand on resources such as hospital beds, theaters, and staff These models help predict demand more accurately on a day-to-day basis..

Henning Schulzrinne from Columbia University in New York and his research group have introduced the concepts for SIP-based application-level mobility [7] [8]. These concepts are very innovative and disruptive by nature, and have already, in part, been proven in the market (such as the inherent mobility offered by commercial VoIP networks). Table 15.1 examines SIP-based application-level mobility. Some of the mobility modes discussed are, however, attributable to the intrinsic mobility on the Internet. These may apply equally well for other VoIP protocols, other than SIP, such as is the case for Skype (though Skype uses SIP gateways as well for PSTN termination).

The preceding statement creates a new Excel workbook. To enter a value in cell A1 of the Excel worksheet, use the following statement:

Sat/C6-41

The next section provides a mapping for the form beans that will be used. The name of the bean is the name that will be used to reference that bean in the session or request scope. The type of the bean is the fully qualified class name of the class that implements the bean. Because we have elected not to place our beans in a package, the type is simply the class name:

=SUBSTITUTE(A1, , )

Channels are set up under the control of call and connection handling mechanisms, and paths are set up and managed on a semi-permanent basis, like transmission resources, under the control of network management mechanisms. However, these concepts evolve towards automatic access by users for the management of their paths (as in the case of leased lines).

Take a quick look at the underlying code of the ViewPriceByTime macro to make sure you understand what is going on. From the Developer tab, select Macros. From the Macro dialog box select the ViewPriceByTime macro and click Edit (see Figure 6-22).

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