New feature extraction method based on the Quantization-based position Weight Matrix (QuPWM) method designed explicitly for multiclass classification on biomedical signals.
Implement a data-driven control for smart aquaculture. The proposed approach will take advantage of the recent developments in computer vision technology to assess and inspect fish behavior and feedback information on fish behavior
We developed a feature extraction method, called QuPWM, for epileptic spikes detection in MEG signals. This method is based on combining the position weight matrix (PWM) method with digital quantization.
New feature extraction method based on the Quantization-based Semi-Classical Signal Analysis designed explicitly for epileptic spikes using Magnetoencephalography (MEG) signals.
We developed New hybrid model for poly(A) signal prediction in human DNA is developed. It contains 8 deep neural networks and 4 logistic regression models. A novel feature generation method is used to extract relevant patterns in the DNA sequences.
Nowadays, there is a recent call to build a human-independent intelligence which can assist clinicians during medical diagnosis.