Semi-automative binary classification workflow

Abstract

SEMI-AUTOMATED BINARY CLASSIFICATION WORKFLOW

MOTIVATION

Nowadays, there is a recent call to build a human-independent intelligence which can assist clinicians during medical diagnosis. In our research, we focus on development of a standartized and tunable workflow for the binary classification problem whithin variuos biological signals (EEG, fMRI, NIRS). This workflow can be openly used by others in their own studies, research and clinical practice.

OBJECTIVES

1. Evaluate efficiency of different classification methods on well- known in community datasets

2. Merge produced code into separate workflows for datasets depending on their dimentionality (single-channel, multi- channel, volumetric)

CHALLENGES

1. Absence of default data formating among researchers which requires human intervention.

2. Optimization of the code architecture and workflow parallelization (choosing among a range of preprocessing steps, feature generation and classification methods.

METHODS

In the central part of the poster one may see a picture of two best performing on fMRI Star-Plus dataset workflows we have inside our generalized workflow for multi-dimensional data. Below we describe other options we provide the user whithin the project.

PREPROCESSING

Frequency filtering

Independent Component Analysis

Smoothing (exponentional, rollong mean)

Global Signal Regression

FEATURE GENERATION

Fast Fourier Transform

Semi-Classical Signal Analysis

UTILIZED CLASSIFIERS

Support Vector Classifier

Logistic Regression

Decision Tree Classifier

K-Nearest Neighbours

Neural Network

Convolutional Neural Network

CONCLUSIONS

We tried to include state of the art practics of brain data analysis and include some novel methods like SCSA. Currently the project is still under development but if you findit interesting and prospectively useful for yourself we suggest to pass our tutorial on single-channel data analysis which is a part of the project and explains the methods behind the workflow.