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

Semptomlardan Yola Çıkarak Diyabet Riskinin Tahmini: ML Modellerinin Performans Karşılaştırması

Obsolete buildout for the EDRN Public Portal

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

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).

This repository contains Agief Prakasa Nurdien's AoL (Assurance of Learning) Case Study for COMP6065001 – Artificial Intelligence course. The project combines keyboard & mouse activity tracking with NLP-based text analysis to provide users with an accessible, interactive tool for ADHD screening and awareness (AoL score: 90, grade: A).

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

📊 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.

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.

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.

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.

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.

Methods for Advance Detection of COVID-19.

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

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

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