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"
Mild Cognitive Impairment Detection from Rey-Osterrieth Complex Figure Copy Drawings using a Contrastive Loss Siamese Neural Network
🧠 Detect MCI from EEG/ERP data using standardized datasets, feature pipelines, and robust validation metrics for reproducible research.
Alzheimer & MCI DeepLearning (CNN) based Diagnosis Model
Task and analysis code for "Linking cognitive integrity to working memory dynamics in the aging human brain"
Open EEG–MCI benchmark in BIDS format with ERP pipelines. Subject-level LOSO validation, reproducible ML/DL baselines, and reports (F1/MCC/AUC).
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