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Rapid Automated Classification of Anesthetic Depth Levels using GPU Based Parallelization of Neural Networks
Peker, Musa; Sen, Baha; Gürüler, Hüseyin (Springer, 2015)The effect of anesthesia on the patient is referred to as depth of anesthesia. Rapid classification of appropriate depth level of anesthesia is a matter of great importance in surgical operations. Similarly, accelerating ...