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

Semptomlardan Yola Çıkarak Diyabet Riskinin Tahmini: ML Modellerinin Performans Karşılaştırması

Research on developing a new method for determining the warning time of Early Warning Signals. Also an attempt at removing window size uncertainty from EWS analysis

Obsolete buildout for the EDRN Public Portal

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

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

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

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

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.

This project uses YOLO for real-time leukemia detection in blood samples and CNNs for classifying brain hemorrhages in MRI scans. It aims to support faster, more accurate medical diagnostics through deep learning.

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.

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).

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

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).

Methods for Advance Detection of COVID-19.

This repository contains an implementation of DISC, an algorithm for learning DFAs for multiclass sequence classification.

This project primarily focuses on addressing the issue of early detection of learning disabilities in students, with a specific focus on dyslexia and attention deficit hyperactivity disorder (ADHD).

This project uses YOLO for real-time leukemia detection in blood samples and CNNs for classifying brain hemorrhages in MRI scans. It aims to support faster, more accurate medical diagnostics through deep learning.