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The objective of this research project, conducted in collaboration with the Policlinico Gemelli, is the development of an automatic system for the analysis of EEG (ElectroEncephaloGram) signals in order to predict seizures in patients resistant to drug treatment.

**The Challenge**

The solution requires the capture and recognition of EEG signal changes typical of the onset of a pre-critical phase. This allows the necessary precautions to be activated to avoid or manage the actual seizure. One of the difficulties to be faced in the development of an automated solution is the strong noise of the EEG signals.

**The Solution**

We filter the EEG signals managing to extract the most relevant features through autoregressive models (AR). Based on the features thus highlighted we build classification models of type Support Vector Machines (SVM), which we train to distinguish between a normal phase and a pre-critical phase.

**Results and Benefits**

The predictive model helps to identify the pre-critical phase of a seizure.

Healthcare & Pharma

Find out how a mathematical model uses electroencephalogram data to predict seizures onset and other adverse events: visit the website!

Forecasts of Adverse Events from Medical Data

Predict the behavior of complex systems to take the best decisions

Forecasting

Identify pre-critical phase from EEG data

Machine learning methodologies, models, algorithms and techniques have become indispensable decision support tools in all industries, thanks to the ever-increasing availability of data. Machine learning models enable prediction, classification, anomaly identification, pattern recognition, time series analysis, in complex systems informally described by large amounts of data.

Deix is able to offer **machine learning-based** algorithmic solutions, thanks to a highly trained team and to the members of the Scientific Committee who have contributed to the development of state-of-the-art machine learning algorithms.

The particularity of Deix is that of **data-driven optimization**, i.e. of appropriately integrating machine learning and artificial intelligence techniques with optimization and control algorithms. The construction of the machine learning model obtained from the available data, which may be **texts, images, videos, historical series** is aimed at **prediction**, **pattern recognition**, **classification,** but it is also functional to the decision-making process above, which is guided by the optimization algorithm. 

In supporting design and management decisions, Deix combines the typical tools of **artificial intelligence** (neural networks, convolutional networks, deep learning, clustering, feature selection, novelty detection) with **optimization algorithms** (constrained and unconstrained) and **optimal control techniques**.

We specialize in creating Machine Learning Models. We develop Machine Learning Solutions, Applications and Algorithms: visit our website!

Adverse Events Prediction

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