MemoryMate is a project that has been started as my moonshot project for ALGOSUP.

[MedIA 2024] This is a code implemention of the joint learning framework proposed in the manuscipt "Joint learning framework of cross-modal synthesis and diagnosis for Alzheimer's disease by mining underlying shared modality information".

Visium SPG AD project (n = 10) using Visium Spatial Proteogenomics (Visium-SPG) on dissections from the inferior temporal cortex (ITC) from Alzheimer's disease cases and controls.

Here is our main codebase for fine-tuning transformers for AD classification and MMSE regression.

project to detect Alzheimer's disease stages from MRI scans using deep learning, featuring api to accept images

Amyloid imaging to prevent Alzheimer's Disease

A Novel Approach for Alzheimer's Classification Utilizing Ensemble Learning on Pre-trained Neural Networks Fine-tuned on Alzheimer's Data

This repo accompanies the Soelter et al., 2023 pre-print

The purpose of this paper is to detect Alzheimer’s Disease using Deep Learning and Machine Learning algorithms on the early basis which is being further optimized using CSA(Crow Search Algorithm). Alzheimer’s is one of kind and fatal. The early detection of Alzheimer’s Disease because of it’s progressive risk and patients all around the world. E…

El proyecto denominado "Implementación de un modelo predictivo basado en redes neuronales convolucionales 3D en el paso de deterioro cognitivo leve a Alzheimer sobre imágenes por resonancia magnética" muestra una estructura de red neuronal convolucional 3D cuyo objetivo es servir como apoyo médico a partir de la detección temprana del Alzheimer

Repository containing the computational code for Single Nucleus RNA Sequencing Demonstrates an Autosomal Dominant Alzheimer’s Disease Profile and Possible Mechanism of Disease Protection manuscript by Almeida et al.

A novel insight into neurological disorders through HDAC6 protein-protein interactions

Aliro: AI-Driven Data Science

Hello! We are an international group of students researching deep learning applications for Alzheimer's disease. We aim to introduce a better model for AD diagnosis. Our names are Fathimah Bajened, Akshat Bhaskar, Hugo Jal Hernández, Abdul Hadi, Brennan Lee, Basit Oliyide, Parth Parikh, Ravi Shah & Neelasha Sudarshan.

Harnessing Genome Wide Association studies to identify biomarkers linked to the early onset of Alzheimer's disease and construct predictive models for the detection of these biomarkers within gene sequences.

A reproducible 3D convolutional neural network with dual attention module (3D-DAM) for Alzheimer's disease classification

Process ADNI study data with adnipy.

A suite of tools for the preprocessing of MRI images and the training of CNNs for the classification of Alzheimer's Disease patients.

Machine Learning models for Alzheimer’s Classification

[JBHI 2024] This is a code implementation of the hybrid-granularity ordinal learning proposed in the manuscript "HOPE: Hybrid-granularity Ordinal Prototype Learning for Progression Prediction of Mild Cognitive Impairment".