Titlebook: Discovery and Representation of Causal Relationships from a Large Time-Oriented Clinical Database: T; The RX Project Robert L. Blum Confere

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Competing Approaches in Economics?” That section concludes with a discussion of one major area for immediate application of this dissertation research: .. Finally, the last section of this chapter presents a list of unfinished tasks. It is intended to expose some of the limitations of the current computer program and to present som

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https://doi.org/10.1007/978-3-642-93235-9Fitting; Medizinische Informatik; Regression analysis; Time; correlation

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The Time-Oriented Database,d contents of the time-oriented database used in this research. An understanding of the database is crucial to understanding the other components of RX. In the following introduction I will review the basic structure of time-oriented databases presented in Chapter 1.

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Statistical Analysis of Longitudinal Data,ge base. The hypothesis may have been obtained either manually from a researcher or automatically from the Discovery Module. Once the statistical model has been formulated, a statistical package is automatically invoked, and the model is tested on the appropriate set of data from the database.

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https://doi.org/10.1007/978-981-19-9845-4d contents of the time-oriented database used in this research. An understanding of the database is crucial to understanding the other components of RX. In the following introduction I will review the basic structure of time-oriented databases presented in Chapter 1.

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Considerations Concerning the Experiment,e Discovery Module or interactively from a researcher. It then generates a medically and statistically plausible model of the hypothesis that it analyzes on appropriate data from the database. Results that are medically and statistically significant are then encoded by it into the RX knowledge base.