Dolores M. Peterson

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The goal of the research being reported is the discovery of useful concepts in temporal medical databases. Building on previous experiments, we introduce TEMPADIS, the Temporal Pattern Discovery System, which uses our Event Set Sequence approach to discover patterns in this type of data. Results are presented for a database of Human Immunodeficiency Virus(More)
The goal of the research being reported is the discovery of useful concepts in temporal medical databases. Building on previous experiments, we introduce TEMPADIS, the Temporal Pattern Discovery System, which uses our Event Set Sequence approach to discover sequential patterns in medical data. We discuss problems unique to mining medical databases and(More)
The goal of the research being reported is the discovery of useful concepts in temporal medical databases. In this paper, we present a sequence building approach, based on the Generalized Sequential Patterns (GSP) Algorithm (Srikant and Agrawal 1996), to discover temporal patterns in this type of data. We show that this pattern discovery is possible by(More)
Aphasic and nonaphasic subjects repeated 24 sentences that varied according to grammatical complexity of the auxiliary. The results revealed that the repetition behavior of both groups was influenced by grammatical complexity. Sentences containing two or three optional auxiliary elements were more difficult to repeat than sentences with one or no optional(More)
Visual acuity of amlyopic eyes, measured under binocular viewing conditions, was improved by reducing the contrast of targets presented to the normal eye. Improvement was also obtained by adjusting the temporal relationship between inputs to the normal and amblyopic eye. Optimal acuity was obtained by alternately presenting targets to the two eyes at rates(More)
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