NYUMedML/CNN_design_for_AD
Code for "Generalizable deep learning model for early Alzheimer’s disease detection from structural MRIs"
This project offers a deep learning model for the early detection of Alzheimer’s disease from structural MRI scans. It takes raw or preprocessed MRI images as input and classifies them into Cognitively Normal, Mild Cognitive Impairment, or Alzheimer's Disease. This tool is designed for clinical researchers, neurologists, or radiologists interested in improving the speed and accuracy of AD diagnosis.
174 stars. No commits in the last 6 months.
Use this if you need a highly accurate and fast method to analyze structural MRI scans for early Alzheimer's disease detection, outperforming traditional volume/thickness models.
Not ideal if you do not have access to MRI data or lack the computational resources for deep learning model training and inference.
Stars
174
Forks
41
Language
Jupyter Notebook
License
AGPL-3.0
Category
Last pushed
Oct 20, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/NYUMedML/CNN_design_for_AD"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
jrieke/cnn-interpretability
🏥 Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer’s Disease
aramis-lab/AD-DL
Classification of Alzheimer's disease status with convolutional neural networks.
Gersha2024/Alzheimer-MRI-Preprocessing-FreeSurfer-SliceSelection-DeepLearning-TransferLearning-EnsembleLearning
🧠 Detect Alzheimer's disease using MRI scans with transfer learning, deep learning, and ensemble...
shreyasgite/dementianet
A longitudinal spontaneous speech (machine learning audio) dataset for dementia diagnosis.
edaaydinea/OP1-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease
This is an optional model development project on a real dataset related to predicting the...