dementia-detection

This repository is related to the thesis paper titled as "ALzheimer's Disease & Dementia Detection From 3D Brain MRI Data Using Deep Convolutional Neural Networks." This thesis paper was accepted and published by IEEE's 3rd INTERNATIONAL CONFERENCE FOR CONVERGENCE IN TECHNOLOGY ( I2CT), PUNE, INDIA - 6-8 APRIL, 2018.

Predicting Dementia Based on Speech Using GPT-3 Text Embeddings.

🏆 HackPrinceton 1st Place (Health Hack + Best Use Machine Learning) - Developed method for Alzheimer’s and Dementia early on-set detection. 💊 Built AWS Lambda backend, NLP classifiers, & integrated software with Amazon Alexa

Code supplement for "Unsupervised multimodal modeling of cognitive and brain health trajectories for early dementia prediction"

Dementia is a neurodegenerative disorder, using this web-app we can predict whether the person is suffering from dementia or not

Cognitive test which is for diagnosing dementia.

A Machine Learning Approach for Cognitive Decline Detection Using Neuroimaging Data Developed a multi-model system to predict brain tumor, dementia, and schizophrenia diseases. Integrated these models into a Flask app for real-time predictions.

Aiginition Longitudinal Biomarker Investigation Of Neurodegeneration

Built a simple AI that looks at brain MRI scans and tells you if there’s no Alzheimer’s, very mild, mild, or moderate signs; right now it gets it right 89% of the time . It runs on EfficientNet-B0, trains fast in Colab, and a streamlit web app where you can upload any MRI and get an instant answer. Everything is open-source

Early dementia detection web app using deep learning and MRI analysis

An application that allows users to predict the risk of a patient having dementia based from their MRI Scan and other medical data using Three Ensemble machine learning methods

AI-powered web app for early stage dementia detection using cognitive screening tests and ensemble ML models

Early dementia detection from biomarker data, comparing deep learning models on tabular clinical features.

Reference architecture and runnable implementation of an AI digital twin and non-invasive BCI for dementia care. What the twin may claim is bounded by the sensing available to it, enforced in code. Research prototype — not a medical device, synthetic data only.

Multimodal dementia risk, progression, and digital-twin-lite model for the CBR Healthy Brain Aging AI Challenge.

A Dementia Probability Diagnostic Application Using Deep Learning

Cognify is a cloud-based AI system developed as a University Final Year Project. It leverages deep learning techniques to analyse MRI images and detect signs of Alzheimer’s Disease (AD)

Binary classification system for dementia risk prediction using non-medical features. ModelX Optimization Sprint submission by IEEE Society, IIT Sri Lanka. Achieves 0.9254 ROC-AUC using only demographic and lifestyle data from NACC dataset

Official implementation of 'Forgotten Words': Benchmarking NeoBERT and BERT for dementia detection in conversational Filipino and English speech using monolingual and bilingual training configurations.

MSc dissertation: Alzheimer's Dementia classification from speech transcripts using Speech Graphs and Graph Convolutional Networks (GCN) with Bio_ClinicalBERT embeddings.