Rapid Automated Classification of Anesthetic Depth Levels using GPU Based Parallelization of Neural Networks

[1]  Musa Peker,et al.  A Comparative Study on Classification of Sleep Stage Based on EEG Signals Using Feature Selection and Classification Algorithms , 2014, Journal of Medical Systems.

[2]  Musa Peker,et al.  Novel approaches for automated epileptic diagnosis using FCBF selection and classification algorithms , 2013 .

[3]  B. B. Zaidan,et al.  An Enhanced Security Solution for Electronic Medical Records Based on AES Hybrid Technique with SOAP/XML and SHA-1 , 2013, Journal of Medical Systems.

[4]  Hamid Behnam,et al.  Monitoring the depth of anesthesia using entropy features and an artificial neural network , 2013, Journal of Neuroscience Methods.

[5]  Nor Ashidi Mat Isa,et al.  Intelligent Medical Disease Diagnosis Using Improved Hybrid Genetic Algorithm - Multilayer Perceptron Network , 2013, Journal of Medical Systems.

[6]  Reza Boostani,et al.  A wavelet-based estimating depth of anesthesia , 2012, Eng. Appl. Artif. Intell..

[7]  Julius Georgiou,et al.  EEG-Based Automatic Classification of ‘Awake’ versus ‘Anesthetized’ State in General Anesthesia Using Granger Causality , 2012, PloS one.

[8]  M. Kertai,et al.  Brain Monitoring with Electroencephalography and the Electroencephalogram-Derived Bispectral Index During Cardiac Surgery , 2012, Anesthesia and analgesia.

[9]  Hossein Rabbani,et al.  Estimation the Depth of Anesthesia by the Use of Artificial Neural Network , 2011 .

[10]  Kenji Suzuki,et al.  Artificial Neural Networks - Methodological Advances and Biomedical Applications , 2011 .

[11]  Xavier Sierra-Canto,et al.  Parallel Training of a Back-Propagation Neural Network Using CUDA , 2010, 2010 Ninth International Conference on Machine Learning and Applications.

[12]  Jinxian Lin,et al.  Accelerating BP Neural Network-Based Image Compression by CPU and GPU Cooperation , 2010, 2010 International Conference on Multimedia Technology.

[13]  Ke Meng,et al.  Accelerating Multi-layer Perceptron based short term demand forecasting using Graphics Processing Units , 2009, 2009 Transmission & Distribution Conference & Exposition: Asia and Pacific.

[14]  Keechul Jung,et al.  Neural Network Implementation Using CUDA and OpenMP , 2008, 2008 Digital Image Computing: Techniques and Applications.

[15]  Mohammad Bagher Shamsollahi,et al.  Estimating the depth of anesthesia using fuzzy soft computation applied to EEG features , 2008, Intell. Data Anal..

[16]  P. Toft,et al.  [Bispectral index for improving anesthetic delivery and postoperative recovery. A survey of a Cochrane review]. , 2008, Ugeskrift for laeger.

[17]  Ömer Kelesoglu,et al.  DETERMINATION OF ANNUAL HEAT LOSS AND REQUIREMENT OF ENERGY IN A REİNFORCED CONCRETE BUILDING BY ARTIFICIAL NEURAL NETWORKS , 2008 .

[18]  Hamdi Melih Saraoglu,et al.  A Fuzzy Logic-Based Decision Support System on Anesthetic Depth Control for Helping Anesthetists in Surgeries , 2007, Journal of Medical Systems.

[19]  Hamdi Melih Saraoglu,et al.  E-Nose System for Anesthetic Dose Level Detection using Artificial Neural Network , 2007, Journal of Medical Systems.

[20]  C. Eswaran,et al.  Automated Detection of Anesthetic Depth Levels Using Chaotic Features with Artificial Neural Networks , 2007, Journal of Medical Systems.

[21]  J. Apfelbaum MILLER??S ANESTHESIA-2-VOLUME SET, 6TH EDITION , 2005 .

[22]  Jeffrey C. Sigl,et al.  Anesthetic Management and One-Year Mortality After Noncardiac Surgery , 2005, Anesthesia and analgesia.

[23]  Paul S. Myles,et al.  Bispectral index monitoring to prevent awareness during anaesthesia: the B-Aware randomised controlled trial , 2004, The Lancet.

[24]  Erik W. Jensen,et al.  EEG complexity as a measure of depth of anesthesia for patients , 2001, IEEE Trans. Biomed. Eng..

[25]  D. Reich,et al.  Development of a Decision Support System to Assist Anesthesiologists in Operating Room , 2000, Journal of Medical Systems.

[26]  P. White,et al.  Electroencephalographic Bispectral Index Correlates with Intraoperative Recall and Depth of Propofol-Induced Sedation , 1997, Anesthesia and analgesia.

[27]  A. Ivankovich,et al.  Sevoflurane triggers malignant hyperthermia in swine. , 1981, Anesthesiology.

[28]  S. Kajan,et al.  COMPUTING OF NEURAL NETWORK ON GRAPHICS CARD , 2010 .

[29]  Rustu Gunturkun,et al.  Estimation of Medicine Amount Used Anesthesia by an Artificial Neural Network , 2009, Journal of Medical Systems.

[30]  P. J. Narayanan,et al.  High Performance Pattern Recognition on GPU , 2008 .

[31]  J. Schumacher,et al.  Chapter 27 – Anesthesia and Analgesia , 2006 .

[32]  Vikram Srinivasan,et al.  EEG BASED AUTOMATED DETECTION OF ANESTHETIC LEVELS USING A RECURRENT ARTIFICIAL NEURAL NETWORK , 2005 .

[33]  Luanne Metz,et al.  For Personal Use. Only Reproduce with Permission from the Lancet , 2022 .