An Android app for recording hypertension-related data.
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Updated
Jun 27, 2024 - Kotlin
An Android app for recording hypertension-related data.
Analysis of 10- and 30-year predicted CVD risk among JHS participants
Lab website
1D blood flow model
A Physiology-Informed ECG Delineation Algorithm Based on Peak Prominence
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.
MARISSA - Magnetic Resonance Imaging Software for Standardization
Non-Invasive Fractional Flow Reserve Estimation using Deep Learning on Intermediate Left Anterior Descending Coronary Artery Lesion Angiography Images
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.
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
Ping Lab Intern Project, Summar, 2022: Link prediction through Graph Neural Network (GNN) model over the Knowledgegraph in the interface of Cardiovascular Disease (CVD) and Drugs.
Disease Prediction and Analyzation of attributes
o²S²PARC implementation of the Cardiovascular Control model developed at the Daniel Baugh Institute, see [original repository](https://github.com/Daniel-Baugh-Institute/CardiovascularControl)
Cardiovascular Risk Prediction - Classification
Code used for data analysis of drug repurposing approach to target inflammation in atherosclerosis
Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement (NeurIPS 2020)
Predicting First-Year Survival after Percutaneous Coronary Interventions: A Machine Learning-Based ShinyApp Web Application in R
Work done during rotation with Coleen McNamara & Stefan Bekiranov in UVA BIMS PhD program
Linking brain phenotypes to cardiovascular risk-factors through GWAS
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