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NeuroLens: Explainable AI for Early Alzheimer’s Detection from MRI and Genetic Biomarkers
NeuroScan AI — Interpretable AI for Early and Accurate Alzheimer’s MRI Staging
Analyzing vocabulary and repetition patterns to study linguistic markers of Alzheimer’s disease.
A 24/7 AI companion that listens, understands, and supports mental well-being instantly.
Early detection saves lives. Our AI classifies brain MRI scans into 4 dementia stages with explainable Grad-CAM visualizations.
A deep learning research initiative that evaluates advanced CNN architectures for the precise staging of Alzheimer’s disease, leveraging MRI analysis to support early detection methodologies.
Using deep learning to understand Alzheimer's stages from brain MRI scans
A Hybrid Approach Using Wav2Vec2 and Support Vector Machines
An AI-based healthcare prototype built with Streamlit and Scikit-learn to demonstrate early Alzheimer’s risk screening using cognitive test scores.
An Explainable Deep Learning Framework for Alzheimer’s Disease Stage Classification from MRI Scans
An interpretable machine-learning framework for genomic risk stratification in Alzheimer’s disease, combining multi-class prediction with confidence-based prioritization to support biological insight.
An explainable deep learning model that classifies Alzheimer’s disease stages from MRI scans and visualizes why predictions are made.
We built an explainable AI that detects early Alzheimer’s risk and predicts disease progression using real biomedical data, offering transparent to support timely, accessible clinical decision making
A Multimodal AI combining ResNet-18 MRI scans & Genetic Risk (APOE) for 96% accuracy. Includes "Glass Brain" heatmaps for full clinical explainability and biological validation.
AI-Powered Early Detection of Alzheimer's and Brain Tumors
We built a CNN-based Alzheimer's MRI classifier using transfer learning and enhanced transparency with Grad-CAM visualizations.
Early Detection, Timely Intervention: AI-Powered Alzheimer's Risk Assessment
RobustHOG: An interpretable ML model using HOG features, PCA, Diffusion Maps, and Logistic Regression to predict Alzheimer’s severity from MRI scans with robustness and statistical validation.
An interpretable machine learning system that predicts Alzheimer’s risk from clinical data and explains key contributing factors to support early detection.
Oasis orchestrates multiple AI capabilities into a unified platform that executes user intent through continuous, personalized intelligence.
ABSTRACT Graphene is one of those materials that feels almost unreal. One atom thick, insanely strong, extremely conductive, flexible, and chemically adaptable.
AI chatbot that offers reminders, conversations, and emotional support to help Alzheimer’s patients stay engaged.
MediScan AI is an advanced AI/ML-powered diagnostic platform that democratizes healthcare by enabling early disease detection through multi-modal medical image analysis and patient data integration.
Trained NN model to predict is there is a problem or not
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