👾 notes and resources on blockchain's maximal extractable value: on the hope of non-predatory free markets in the metaweb

Augmentative and Alternative Communication (AAC) system with text-to-speech for the browser

Detecting Autism Spectrum Disorder in Children With Computer Vision - Adapting facial recognition models to detect Autism Spectrum Disorder

Deep neural network trained to detect eye contact from facial image

A curated list of awesome resources for Autism Spectrum Disorder and Asperger's Syndrome

This project describes the necessary code to implement an EEG-based emotion recognition using SincNet [Ravanelli & Bengio 2018] including data from individuals diagnosed with Autism (ASD). For more details and data request send an email to the authors and contributors Juan Manuel Mayor Torres (juan.mayortorres@unitn.it) and Mirco Ravanelli (Mila)

AssemblyNet: 3D Whole Brain MRI segmentation pipeline

GAIA - Guidelines for Accessible Interfaces for Autistics

Code for processing and managing data for EEG-based emotion recognition of individuals with and without Autism. EEG and other clinical data were collected in StonyBrook Social Competence Treatment Lab, for data request evaluation please contact professor Matthew D. Lerner matthew.lerner@stonybrook.edu

A Chatbot Game for Autistic Children 一款为孤独症孩子设计的聊天机器人游戏

Create reusable cards for quick access when non-verbal communication is needed.

Repository for the Brainhack School 2020 team working with fMRI and ABIDE data to train machine learning models.

A curated list of awesome technologies related to Autism Spectrum Disorder (ASD)

Code respository for AutSPACEs: the Autistica/Turing citizen science platform

Deep learning methods for feature selection in gene expression autism data.

Supporting system of behavioral therapy of people with autism. Check starter kit:

The project aims early detection of 'Autism' and 'ADHD' through a web platform fueled by machine learning.

productivity tool for neurodivergent people

This script automates the download of preprocessed brain imaging data from the ABIDE dataset, focusing on a specific derivative, preprocessing pipeline, and noise-removal strategy. It filters participants by diagnosis (autism or controls) and downloads relevant data, streamlining research on autism spectrum disorder.