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- W2182045498 abstract "Medical prognosis has played an increasing role in health, namely in the critical care medicine. These factors have induced the medical community to take a more active interest in developing models for mortality prediction based on Artificial Intelligence (AI) techniques [1]. that make possible the doctors pro-active action. In this context, the existence of large Databases (DB) containing Intensive Care Units (ICU) clinical information, motivate and enable the application of Data Mining (DM) techniques, in a Knowledge Discovery Database process (KDD). to induce prediction models of organ failure in a much more efficient way than other approaches (e.g.. Logistic Regr es sion) [2]. Clinical guidelines carry medical evidence to the point of practice. As evidence is not always available, many guidelines do not provide recommendations for all clinical situations encountered in practice. We propose a decisions making system for exploring physicians' therapeutic decisions with data mining techniques to fill knowledge gaps. The various data mining techniques are explored in this paper for the proposed system" @default.
- W2182045498 created "2016-06-24" @default.
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- W2182045498 date "2014-01-01" @default.
- W2182045498 modified "2023-09-27" @default.
- W2182045498 title "Therapeutic Decisions Making System Using Data Mining Techniques: A Review" @default.
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- W2182045498 hasPublicationYear "2014" @default.
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