Autism Classifier #4
Description
Title
Autism-classification
Leaders
Sebastían Mesh Henriques
Emilio Recart
Collaborators
No response
Brainhack School 2023 Hub
Humai
Project Description
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by persistent deficits in social communication and interaction, as well as restricted and repetitive patterns of behavior, interests, or activities. Early and accurate diagnosis of ASD is crucial for timely intervention and support. However, diagnosing ASD can be challenging due to the complexity and heterogeneity of the disorder. Nowadays, the diagnosis of ASD relies on clinical observations.
In recent years, advancements in neuroimaging techniques, particularly functional magnetic resonance imaging (fMRI), have enabled researchers to investigate the neural mechanisms underlying ASD. Functional connectomes, which capture the functional interactions between different brain regions, have emerged as a valuable tool for understanding the brain connectivity patterns associated with ASD. Machine learning techniques, when applied to functional connectome data, have shown promise in assisting with the diagnosis of ASD.
The aim of this research is to investigate the application of machine learning algorithms for Autism Spectrum Disorder (ASD) diagnosis. The study aims to evaluate the performance of machine learning models in classifying individuals with ASD and typically developing individuals based on functional connectome data. Furthermore, the research seeks to assess the potential of functional connectome-based machine learning models as a diagnostic tool for ASD. By analyzing these data, the study aims to contribute to the development of early detection methods and accurate diagnosis of ASD, which could have a significant impact on intervention and treatment for individuals affected by this disorder.
Link to project repository/sources
https://github.com/SMESCH1/Autism-classification-BrainHack
Goals for the Project
To investigate the application of machine learning algorithms for ASD diagnosis
To evaluate the performance of machine learning models in classifying individuals with ASD and typically developing individuals based on functional connectome data.
To assess the potential of functional connectome-based machine learning models as a diagnostic tool for ASD
Deliverables
A Github repository with the script of the project
A jupyter notebook of the analysis codes and visualizations
Skills
- Python Advanced
- Machine Learning applied to fMRI data
- Git and GITHUB commands
- Preprocessing
Data to use
No response
Type
pipeline_development
Development status
1_basic structure
Topic
machine_learning
Tools
fMRIPrep
Programming language
Python
Modalities
fMRI
Anything else?
No response