Vulnerability-Lookup facilitates quick correlation of vulnerabilities from various sources, independent of vulnerability IDs, and streamlines the management of Coordinated Vulnerability Disclosure (CVD).
This repo contains the R microshades package, which contains a color blind accessible color palette with 30 unique colors and functions for applying these colors to microbiome data.
Compute centroidal Voronoi tessellations in 2D and 3D using the GPU.
A Python client for the Global CVE Allocation System.
Vultron is a protocol for Coordinated Vulnerability Disclosure
Content for the CERT Guide to Coordinated Vulnerability Disclosure
Heartbeat Sound Segmentation and Classification. Implemented ways to clean noisy hearbeat sounds in MATLAB and later trained ML models to classify the hearbeat sounds into diseased and normal categories
This repo includes the pipeline used to link and curate CVD PREVENT audit data to HES and death registration data into two tables. These are subsequently sent to OHID for analysis and publication.
image segmentation for SVD graphene SEM images
Register `cividis` with matplotlib, a color map optimized for color vision deficiency, as published in Nuñez, et al. (2018), PLoS ONE 13(7): e0199239 .
A package for running experiments with VAEs for ECG data, including a supervised head designed for survival analysis of cardiovascular disease events.
Centroidal Voronoi Diagram of a mesh's surface using an iterative discrete clustering algorithm on graphs.
This demo is developed using PIC18-Q10 family MCU and Curiosity Nano development board. The demo demonstrates the usage of ADCC with hardware CVD technique and PWM peripherals of PIC18F47Q10 MCU to control DC motor through capacitive touch interface.
Cystatin C and Cardiovascular Disease: A Mendelian Randomization Study.
Arduino sketch for wearable prototype to assist with colour identification.
Monitoring application for Arduino based wearable prototype to assist with colour identification.
Classification of Cardiovascular Disorders using machine learning, Data Analysis of NHANES dataset and Visualizaiong the results
Predicting heart disease risk using combined UCI data and machine learning
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