A collection of extension methods for validating method arguments in order to spot bugs as quickly as possible.
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Updated
Aug 9, 2022 - C#
A collection of extension methods for validating method arguments in order to spot bugs as quickly as possible.
A Time series Data modelling to forecast Gambling Addiction Signs in Players using K-Means Clustering, ARIMA/SARIMA and LSTM to forecast wagering patterns
Obsolete buildout for the EDRN Public Portal
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
EDRN's knowledge using the Resource Description Format (RDF)
Using Image Processing and both classical and brand-new Machine Learning techniques such as SVM, k-NN, XGBoost, and also LSTM; we are trying to predict beforehand the driver's drowsiness and warn him/her by an alert before any crash happened.
Kvasir-SEG: A Segmented Polyp Dataset
Methods for Advance Detection of COVID-19.
Deep Learning Models for the Early Detection of Parkinson’s Disease using the motor-based symptoms.
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).
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.
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.
Addresses the problem of reconstructing images acquired by diffuse optical tomography 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.
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 repository contains an implementation of DISC, an algorithm for learning DFAs for multiclass sequence classification.
📊 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.
Classification of Alzheimer's Disease stages from Magnetic Resonance Images using Deep Learning
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