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Yogesh MJ's Projects

3.eeg_recognation icon 3.eeg_recognation

Python (deep learning and machine learning) for EEG signal processing on the example of recognizing the disease of alcoholism

ad-dl icon ad-dl

Framework for the reproducible classification of Alzheimer's disease using deep learning

ad-ml icon ad-ml

Framework for the reproducible classification of Alzheimer's disease using machine learning

ai-for-medical-diagnosis icon ai-for-medical-diagnosis

This repo contain my assignment notebooks for the Coursera AI for Medicine Specialization course. The link to the course: https://www.coursera.org/specializations/ai-for-medicine

ai-for-medicine icon ai-for-medicine

This repo contains my assignment solutions of AI for Medicine Specialization on Coursera

ai-for-medicine-specialization icon ai-for-medicine-specialization

I have completed this specialization from Coursera by deeplearning.ai. I have uploaded the solutions of the assignments in this repo.

awesome-healthcare-ai icon awesome-healthcare-ai

A curated list of awesome open source healthcare tools, algorithms, datasets and research papers.

awesome-neuroscience icon awesome-neuroscience

A curated list of awesome neuroscience libraries, software and any content related to the domain.

basic-mathematics-for-machine-learning icon basic-mathematics-for-machine-learning

The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI

clinica icon clinica

Software platform for clinical neuroimaging studies

cncc-2019 icon cncc-2019

Computational Neuroscience Crash Course (CNCC 2019)

cncc-2020 icon cncc-2020

Computational Neuroscience Crash Course (University of Bordeaux, 2020)

cnns-on-chb-mit icon cnns-on-chb-mit

The project is about applying CNNs to EEG data from CHB-MIT to predict seizure

covid19-nmt icon covid19-nmt

Multi-lingual & multi-domain (specialisation for biomedical data) translation model

deepbrainnet icon deepbrainnet

Convolutional Neural Network trained for age prediction using a large (n=11,729) set of MRI scans from a highly diversified cohort spanning different studies, scanners, ages, ethnicities and geographic locations around the world.

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