cfDNAPro specializes in standardized and robust cfDNA fragmentomic analysis
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Updated
Aug 12, 2024 - R
cfDNAPro specializes in standardized and robust cfDNA fragmentomic analysis
Open source Artificial Intelligence for COVID-19 detection/early detection. Includes Convolutional Neural Networks (CNN) & Generative Adversarial Networks (GAN)
Fraud Detection for VoIP. Use SentryPeer® HQ to help prevent VoIP cyberattacks and fraudulent VoIP phone calls (toll fraud) at https://sentrypeer.com
proposed early detection method for parkinson's disease using deep learning on MRI dataset
Deep Learning Models for the Early Detection of Parkinson’s Disease using the motor-based symptoms.
Kvasir-SEG: A Segmented Polyp Dataset
This repository contains an implementation of DISC, an algorithm for learning DFAs for multiclass sequence classification.
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
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.
Heterogeneous Graph Attention Networks for Early Detection of Rumors on Twitter (IJCNN 2020)
Addresses the problem of reconstructing images acquired by diffuse optical tomography using deep learning.
Methods for Advance Detection of COVID-19.
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).
A collection of extension methods for validating method arguments in order to spot bugs as quickly as possible.
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.
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
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.
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).
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