There are 5 repositories under cardiovascular topic.
An Android app for recording hypertension-related data.
Full HRV analysis of Arduino pulse sensor, using Python signal processing and time series techniques. Chaotic, Fourier, Wavelet, Regression, Neural Net.
R package for Cardiovascular Risk Dataset and Data generation script
Cardioinformatics: the nexus of bioinformatics and precision cardiology
Non-Invasive Fractional Flow Reserve Estimation using Deep Learning on Intermediate Left Anterior Descending Coronary Artery Lesion Angiography Images
Cardiovascular Risk Prediction - Classification
Code used for data analysis of drug repurposing approach to target inflammation in atherosclerosis
CTAMACE is a web application which can be used to predict major cardiovascular events (MACE) two years following coronary multidetector computed tomography (MDCT) using combined anatomical coronary findings and clinical features
Predicting First-Year Survival after Percutaneous Coronary Interventions: A Machine Learning-Based ShinyApp Web Application in R
A neural network for image segmentation of cardiovascular anatomies. MOVED to AIS Training Codeset, Jan 3, 2020.
Web-based parametric aortic leaflet generator
A Comparison Of Machine Learning Models And Artificial Neural Networks For Detecting The Presence Of Cardiovascular Disease
Free open source Model Library designed to evaluate human physiological evolution in adulthood, childhood, neonatal and fetal life in the face of the occurrence of cardiovascular and respiratory anomalies or different clinical practices.
Optimization framework for automated patient-specific tuning of cardiovascular circulatory models
Analysis of 10- and 30-year predicted CVD risk among JHS participants
A Physiology-Informed ECG Delineation Algorithm Based on Peak Prominence
R code for the data managment and statistical analysis performed for Association between B-Blockers and Outcomes in HFpEF - Current Insights from the SwedeHF Registry.
Disease Prediction and Analyzation of attributes
Maps the STAFF III Database of ECG data annotations file from one line per patient to one line per file
Cost-Effectiveness of a Workplace Ban on Sugar-Sweetened Beverage Sales
Analysis of patient data from a kaggle dataset to assess if tall people's risk of developing cardiovascular disease was higher than short people's.
An auto-encoder for the heart 2.5-D CT images for dimension reduction
Ping Lab Intern Project, Summar, 2022: :octocat: Link prediction through Graph Neural Network (GNN) model over the Knowledgegraph in the interface of Cardiovascular Disease (CVD) and Drugs.
CardioPulse ❤️🩺 is an Android app using machine learning to predict cardiovascular (heart) diseases. Created as a final year project by University of Sialkot students, it combines predictive modeling with Firebase cloud storage. The app offers personalized health assessments and intuitive tracking for early detection and better health outcomes.
Cardiovascular-Health-Diagnostics — це віконний додаток, призначений для діагностики серцево-судинних порушень на основі результатів аналізів кардіограм. Цей інструмент може бути корисним як для медичних спеціалістів, так і для пацієнтів, допомагаючи вчасно виявляти можливі відхилення від норми та ініціювати відповідне лікування.
LaTeX source file for my Computer Science Thesis "Clinical Data Management Processes and Predictive Machine Learning Models Development for Diagnosis and Rehabilitation in the Cardiovascular Domain", which spans over 100 pages. Research was conducted in collaboration with the multinational company Dedalus
o²S²PARC implementation of the Cardiovascular Control model developed at the Daniel Baugh Institute, see [original repository](https://github.com/Daniel-Baugh-Institute/CardiovascularControl)
Work done during rotation with Coleen McNamara & Stefan Bekiranov in UVA BIMS PhD program