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Anesthesia is a branch of medical science generally applied to patients who need surgery or painful acts. Research in this field has brought many changes by decreasing the mortality rate that is why in this work, we propose a computer aided diagnosis system based on Support Vector Machines (SVM) aiming to help doctors in the pre-anesthetic examination. For that, a new database has been obtained with...
Random Forest RF is a successful technique of ensemble prediction that uses the majority voting or an average depending on the combination. However, it is clear that each tree in a random forest can have different contribution to the treatment of some instance. In this paper, we show that the prediction performance of RF's can still be improved by replacing the GINI index with another index (twoing...
Before the routine anesthesia, an airway examination must be performed during the pre-anesthetic examination for all patients who need a surgical operation in order to decide whether the tracheal intubation is easy or hard. In the field of anesthesia and intensive care, many works have been performed in order to reduce as much as possible the anesthetic risks and the mortality rate as well as to provide...
Classification systems have been widely applied in different fields such as medical diagnosis. Interpretability represents the most important driving force behind the implementation of fuzzy-based classifiers for medical application problems. Neuro-fuzzy classification approaches aim at creating fuzzy classification rules from data. The simplest model is The NEFCLASS; it is able to learn fuzzy rules...
The semi-supervised learning has been widely applied in many fields such as medical diagnosis, pattern recognition. The semi supervised learning methods are used to employ unlabelled data in addition to labelled data for better classification of large data sets, where only a small number of labelled examples is available. Ensemble Methods are considered as an effective solution to the problem of dimensionality...
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