Obsolete buildout for the EDRN Public Portal

Early Diabetes Diagnosis Using a Low-Complexity Deep Learning Model with Feature Reduction

VSPsnap is a collection of R and Python code for Gaussian Process regression in a kriging-like setting (i.e. two features (X,Y) and a target (Z)) - with a focus on SARS-CoV2 data (genomic/IR/FR).

Built an end-to-end deep learning pipeline using ResNet-50 to classify retinal images into five stages of Diabetic Retinopathy. Applied transfer learning, image preprocessing, and AUC-based evaluation on the APTOS 2019 Kaggle dataset, achieving a 94% validation AUC—offering real-world potential in clinical diagnosis automation.

A Time series Data modelling to forecast Gambling Addiction Signs in Players using K-Means Clustering, ARIMA/SARIMA and LSTM to forecast wagering patterns

EDRN's knowledge using the Resource Description Format (RDF)

📊 Multiple Disease Prediction System 🏥 An intelligent healthcare system for predicting and diagnosing multiple diseases using machine learning and data analysis. Empowering early detection and better patient care. Disease Prediction: Predict the likelihood of various diseases, including heart diseases, diabetes, and more.

A collection of extension methods for validating method arguments in order to spot bugs as quickly as possible.

Early Detection of Diabetic Kidney Disease using Contrast Enhanced Ultrasound Perfusion Parameters. Explore perfusion models (Lagged Normal, Log-Normal, Gamma Variate), compare their effectiveness, and analyze their application to diabetic and control cases.

Heart Disease Prediction Using Machine Learning is a logistic regression model that predicts heart disease based on medical data. It analyzes features like age and cholesterol, achieving 85.24% training accuracy and 80.49% testing accuracy, facilitating early detection for timely intervention.

Amburgey SM, AA Yackel Adams, B Gardner, B Lardner, AJ Knox, and SJ Converse. 2021. Tools for increasing visual encounter probabilities for invasive species removal: a case study of brown treesnakes. Neobiota 70:107-122.

Classification of Alzheimer's Disease stages from Magnetic Resonance Images using Deep Learning

This repository houses a workflow that uses biological feature trees to segregate cancer RNA-seq datasets, then it trains machine learning models to predict the presence or absence of known, cancer-associated DNA-level mutations.

EDRN Production Program for the Public/Private Portal (P5)

Breast cancer histopathology image segmentation using U-Net. This repository implements U-Net for accurate segmentation of cancerous regions. It includes data augmentation, mixed precision training, checkpointing, and evaluation metrics like Dice score to improve model performance.

Methods for Advance Detection of COVID-19.

Addresses the problem of reconstructing images acquired by diffuse optical tomography using deep learning.

Multiclass Skin lesion localization and Detection with YOLOv7-XAI Framework with explainable AI

Heterogeneous Graph Attention Networks for Early Detection of Rumors on Twitter (IJCNN 2020)