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Preface; Organization; Contents; Plenary Lectures I
Session I: BIOMEDICAL SIGNAL PROCESSING 1; 1 Using machine learning tool in classification of breast cancer; Abstract.; Keyword; 1 Introduction; 2 Methods; 2.1 Wisconsin Breast Cancer Database (WBCD; 2.2 Design of Artificial Neural Network for BreastCancer Classification; 3 Results and discussion; 3.1 Predictive ability of neural network architecturewith different number of hidden layers; 4 c onclusion
2 MULTISAB project: a web platform based on specialized frameworks for heterogeneous biomedical time series analysis
an architectural overviewAbstract.; Keywords:; 1 Introduction; 2 Processing frameworks; 2.1 Common signal features framework; 2.2 Data handling framework; 2.3 Specialized biomedical time series analysis frameworks; 4 Signal visualization; 3 Database; 5 Discussion and conclusion; Conflict of Interest; Acknowledgements; References
3 Short-term variations of parameters of heart rate variability in subjects with mild hypertension and normotensive subjects during preoperative periodAbstract; Introduction; Methods and subjects; Keywords; Results; Discussion; Conclusion; 4 Cardiac pulse waves modeling and analysis in laser Doppler perfusion signals of the skin microcirculation; Abstract.; 1 Introduction; 2 Materials and methods; 2.1 Dataset; 2.2 Experimental setting; 2.3 Gaussian-based cardiac pulse waves modeling; 3 Results; 4 Conclusion; Acknowledgement; References
5 Discrimination of Psychotic Symptoms from Controls Through Data Mining Methods Based on Emotional Principle ComponentsAbstract.; Keywords:; 1 Introduction; 2 Methods; 2.1 Data Collection; 2.2 Feature Extraction; 2.3 Data Mining Methods for Emotion Recognition; 2.4 Performance Criteria; 3 Results; 4 Discussion and Conclusion; Acknowledgements; References; 6 Differences in temporal gait parameters between multiple sclerosis and healthy people; Abstract.; Keywords:; 1 Introduction; 2 Methods; 3 Results; 4 Summary and conclusions; References
7 An Adaptive Scheme for X-ray Medical Image Denoising using Artificial Neural Networks and Additive White Gaussian Noise Level Estimation in SVD DomainAbstract.; Keywords:; 1 Introduction; 2 Singular r Value Dec composition n and Noise Level E stimation; 3 O verview of M Multilayer P Perceptron; 4 Adaptive Image Denoising; 5 Results and Discussion; 6 Conclusion; References; 8 Using Neural Networks and Ensemble Techniques based on Decision Trees for Skin Permeability Prediction; Abstract.; Keywords:; 1 Introduction; 2 Methods
Session I: BIOMEDICAL SIGNAL PROCESSING 1; 1 Using machine learning tool in classification of breast cancer; Abstract.; Keyword; 1 Introduction; 2 Methods; 2.1 Wisconsin Breast Cancer Database (WBCD; 2.2 Design of Artificial Neural Network for BreastCancer Classification; 3 Results and discussion; 3.1 Predictive ability of neural network architecturewith different number of hidden layers; 4 c onclusion
2 MULTISAB project: a web platform based on specialized frameworks for heterogeneous biomedical time series analysis
an architectural overviewAbstract.; Keywords:; 1 Introduction; 2 Processing frameworks; 2.1 Common signal features framework; 2.2 Data handling framework; 2.3 Specialized biomedical time series analysis frameworks; 4 Signal visualization; 3 Database; 5 Discussion and conclusion; Conflict of Interest; Acknowledgements; References
3 Short-term variations of parameters of heart rate variability in subjects with mild hypertension and normotensive subjects during preoperative periodAbstract; Introduction; Methods and subjects; Keywords; Results; Discussion; Conclusion; 4 Cardiac pulse waves modeling and analysis in laser Doppler perfusion signals of the skin microcirculation; Abstract.; 1 Introduction; 2 Materials and methods; 2.1 Dataset; 2.2 Experimental setting; 2.3 Gaussian-based cardiac pulse waves modeling; 3 Results; 4 Conclusion; Acknowledgement; References
5 Discrimination of Psychotic Symptoms from Controls Through Data Mining Methods Based on Emotional Principle ComponentsAbstract.; Keywords:; 1 Introduction; 2 Methods; 2.1 Data Collection; 2.2 Feature Extraction; 2.3 Data Mining Methods for Emotion Recognition; 2.4 Performance Criteria; 3 Results; 4 Discussion and Conclusion; Acknowledgements; References; 6 Differences in temporal gait parameters between multiple sclerosis and healthy people; Abstract.; Keywords:; 1 Introduction; 2 Methods; 3 Results; 4 Summary and conclusions; References
7 An Adaptive Scheme for X-ray Medical Image Denoising using Artificial Neural Networks and Additive White Gaussian Noise Level Estimation in SVD DomainAbstract.; Keywords:; 1 Introduction; 2 Singular r Value Dec composition n and Noise Level E stimation; 3 O verview of M Multilayer P Perceptron; 4 Adaptive Image Denoising; 5 Results and Discussion; 6 Conclusion; References; 8 Using Neural Networks and Ensemble Techniques based on Decision Trees for Skin Permeability Prediction; Abstract.; Keywords:; 1 Introduction; 2 Methods