Code for "Generalizable deep learning model for early Alzheimer’s disease detection from structural MRIs"

[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".

Alzheimer prediction using Ensemble Transfer Learning

A responsive web application that helps members with Mild Cognitive Impairment keep track of their daily routines. This was a class project in partnership with the Aware Home at Georgia Tech under CS 7470 - Ubiquitous Computing taught by Dr. Thomas Ploetz.

Thesis project with title: "Cognitive decline detection using speech features: A machine learning approach"

Listening Between the Lines: An explainable multimodal framework for MCI detection from spontaneous speech. Leverages Selective State Space Models (Mamba) and Gated Fusion to integrate linguistic disfluencies and eGeMAPS biomarkers across multi-corpus benchmarks (Pitt, ADReSS, TAUKADIAL)

Correlation-edge sampling of CAT12 gray matter maps for AD/MCI classification using structural MRI.

Open EEG–MCI benchmark in BIDS format with ERP pipelines. Subject-level LOSO validation, reproducible ML/DL baselines, and reports (F1/MCC/AUC).

AI-driven healthcare project for early prediction of conversion from Mild Cognitive Impairment (MCI) to Alzheimer's disease (AD). The system integrates OCR and NLP techniques to extract clinical information from handwritten medical records and leverages Machine Learning and Deep Learning models for neuroimaging-based analysis and prediction.

Mild Cognitive Impairment Detection from Rey-Osterrieth Complex Figure Copy Drawings using a Contrastive Loss Siamese Neural Network

Reproducible analysis code and aggregated outputs for a VR-based cognitive screening tool with integrated eye tracking (AD, MCI, and controls).

Alzheimer & MCI DeepLearning (CNN) based Diagnosis Model

Task and analysis code for "Linking cognitive integrity to working memory dynamics in the aging human brain"